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Science Citation Index Expanded",{"EN":61,"VI":62},"SCIE database","Cơ sở dữ liệu SCIE","scie",[65,66],"SCIE","ISI","https:\u002F\u002Fmjl.clarivate.com\u002Fsearch-results?issn=1598-6446",[69],"e74ee2cf-73af-4a18-b9f2-e019f875caa2",{"id":71,"indexDatabase":72,"url":82,"indexYears":83,"academicFieldIds":84,"indexDatabaseRanking":87},"8516cf07-c8a6-4b34-a757-796bf9e9125f",{"id":73,"createTime":22,"updateTime":22,"relativeEntities":74,"label":75,"description":77,"key":79,"publicationTags":80,"standard":22},"3c7051d4-eb7d-4c57-a56b-36fc74c5d1e9",[],{"EN":76,"VI":76},"Scopus - Elsevier",{"EN":76,"VI":78},"Cơ sở dữ liệu Scopus thuộc Elsevier","scopus",[81],"SCOPUS","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F25479","2003-2025",[85,86],"212b8bab-be53-49b1-9ceb-c528868800fc","cd7e8237-7356-41bf-8ef9-9ae6051e5be0","SCOPUS__Q2",{"impactFactor":23,"impactFactorByYear":89,"i10Index":91,"i10IndexLast5Year":92,"totalPublication":93,"totalPublicationByYear":94,"totalCitation":110,"totalCitationByYear":111,"totalCitationPerPublication":114,"totalCitationPerPublicationByYear":115,"hindexLast5Year":91,"hindex":91},{"2022":90},0.02,2,1,1871,{"2003":92,"2009":95,"2010":96,"2011":97,"2012":98,"2013":99,"2014":100,"2015":99,"2016":101,"2017":102,"2018":103,"2019":104,"2020":105,"2021":106,"2022":107,"2023":108,"2024":109},57,79,84,75,81,86,105,154,145,212,151,134,187,192,46,61,{"2003":112,"2020":113},47,14,0.03,{"2003":112,"2020":116},0.09,"JOURNAL",{"meta":119,"data":121},{"total":120},"2428",[122,287,392,510,626,890,1093,1225,1473,1594],{"id":123,"createTime":124,"updateTime":125,"relativeEntities":126,"slug":127,"properties":128,"entityType":138,"verifyStatus":139,"verifyTime":140,"verifyNote":141,"languages":22,"translateLanguages":142,"viewCount":23,"primaryUrl":144,"fullTextUrl":22,"authors":145,"publicationType":230,"publisherRelationship":231,"citationCount":22,"citationInfo":22,"publishDate":283,"publishYear":284,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":285,"openAccess":22,"references":22,"isForceReanalyzing":286},"60039363-0dbf-4925-9675-89f6ce6a9f33","2024-01-18T16:40:51.283+00:00","2026-09-08T12:15:01.105+00:00",[],"Prescribed-Performance-tangent-Barrier-Lyapunov-Function-for-Adaptive-Neural-Backstepping-Control-of-Variable-Stiffness-Actuator-with-Input-and-Output-Constraints",{"abstract":129,"title":131,"references":134,"doi":136},{"EN":130},"Due to the complexity of modeling and the strong transmission coupling, the rich background of rigid actuator control has not been transferred to variable stiffness actuator (VSA). Therefore, most model-based control techniques developed for VSA require feedback linearization first. Alternatively, VSA can use non-model-based control techniques such as PD control, but it does not show strong robustness under disturbances. This paper is concerned with designing a novel adaptive neural network backstepping control scheme without using feedback linearization for a special VSA with saturation inputs, output constraints, and disturbances. Firstly, for ensuring the VSA with lower tracking error and higher security, the prescribed performance-tangent barrier Lyapunov function (PP-TBLF) is introduced to handle the prescribed output performance constraints. Subsequently, the Chebyshev neural network and the Nussbaum-type function are exploited to approximate the unknown nonlinearities and unknown gains. Meanwhile, the inverse hyperbolic sine function tracking differentiator is utilized to solve the “explosion of complexity” caused by the differentiation of virtual inputs and also approximate the complex partial derivatives caused by the auxiliary control signals. Finally, the stability of the whole scheme is proved by the Lyapunov criterion. The simulation results illustrate the raised control scheme’s feasibility and show a better closed-loop behavior relative to that obtained using a classic PD controller.",{"EN":132,"VI":133},"Prescribed Performance-tangent Barrier Lyapunov Function for Adaptive Neural Backstepping Control of Variable Stiffness Actuator with Input and Output Constraints","Hàm Lyapunov rào chắn tiếp tuyến với hiệu năng chỉ định cho điều khiển backstepping nơ-ron thích nghi của cơ cấu chấp hành độ cứng biến đổi có ràng buộc đầu vào và đầu ra",{"VOID":135},"B. Vanderborght, A. Albu-Schaeffere, A. Bicchi, E. Bürdet, D. G. Caldwell, R. Carloni, M. Catalano, O. Eiberger, W. Friedl, G. Ganesh, M. Garabini, M. Grebenstein, G. Grioli, S. Haddadin, H. Hoppner, A. Jafari, M. Laffranchi, D. Lefeber, F. Petit, S. Stramigioli, N. Tsagarakis, M. van Damme, R. van Ham, L. C. Visser, and S. Wolf, “Variable impedance actuators: A review,” Robotics and Autonomous Systems, vol. 61, no. 12, pp. 1601–1614, December 2013.\nS. Wolf, G. Griolie, O. Eiberger, W. Friedl, M. Grebenstein, H. Höppner, E. Bürdet, D. G. Caldwell, R. Carloni, M. G. Catalano, D. Lefeber, S. Stramigioli, N. Tsagarakis, R. van Ham, B. Vanderborght, L. C. Visser, A. Bicchi, and A. Albu-Schäffer, “Variable stiffness actuators: Review on design and components,” IEEE\u002FASME Transactions on Mechatronics, vol. 21, no. 5, pp. 2418–2430, 2016.\nJ. M. Gandarias, Y. Wang, A. Still, A. J. García-Cerezo, J. M. Gómez-de-Gabriel, and H. A. Wurdemann, “Open-loop position control in collaborative, modular Variable-Stiffness-Link (VSL) robots,” IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1772–1779, May 2020.\nH. Q. Vu, X. Yu, F. Iida, and R. Pfeifer, “Improving energy efficiency of hopping locomotion by using a variable stiffness actuator,” IEEE\u002FASME Transactions on Mechatronics, vol. 21, no.1, pp. 472–486, February 2016.\nA. Zhakatayev, M. Rubagotti, and H. A. Varol, “Energy-aware optimal control of variable stiffness actuated robots,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 330–337, April 2019.\nD. J. Braun, V. Chalvet, T.-H. Chong, S. S. Apte, and N. Hogan, “Variable stiffness spring actuators for low-energy-cost human augmentation,” IEEE Transactions on Robotics, vol. 35, no. 6, pp. 1435–1449, December 2019.\nY. Liu, X. Liu, Z. Yuan, and J. Liu, “Design and analysis of spring parallel variable stiffness actuator based on antagonistic principle,” Mechanism and Machine Theory, vol. 140, pp. 44–58, October 2019.\nR. Mengacci, M. Garabini, G. Grioli, M. G. Catalano, and A. Bicchi, “Overcoming the torque\u002Fstiffness range tradeoff in antagonistic variable stiffness actuators,” IEEE\u002FASME Transactions on Mechatronics, vol. 26, no. 6, pp. 3186–3197, December 2021.\nA. Fagiolini, M. Trumic, and K. Jovanovic, “An input observer-based stiffness estimation approach for flexible robot joints,” IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1843–1850, April 2020.\nG. Grioli, S. Wolf, M. Garabini, M. Catalano, E. Burdet, D. Caldwell, R. Carloni, W. Friedl, M. Grebenstein, M. Laffranchi, D. Lefeber, S. Stramigioli, N. Tsagarakis, M. van Damme, B. Vanderborght, A. Albu-Schaeffer, and A. Bicchi, “Variable stiffness actuators: The user’s point of view,” The International Journal of Robotics Research, vol. 36, no. 6, pp. 727–743, May 2015.\nK. Li, H. Jiang, S. Wang, and J. Yu, “A soft robotic fish with variable-stiffness decoupled mechanisms,” Journal of Bionic Engineering, vol.15, no. 4, pp. 599–609, July 2018.\nJ. Geeroms, L. Flynn, R. Jimenez-Fabian, B. Vanderborght, and D. Lefeber, “Energetic analysis and optimization of a MACCEPA actuator in an ankle prosthesis,” Autonomous Robots, vol. 42, no. 1, pp. 147–158, January 2018.\nM. Zhang, L. J. Fang, F. Sun, and K. Oka, “A novel wire-driven variable stiffness joint based on a permanent magnetic mechanism,” Journal of Mechanisms and Robotics, vol. 11, no. 5, December 2020.\nS. Wolf and J. E. Feenders, “Modeling and benchmarking energy efficiency of variable stiffness actuators on the example of the DLR FSJ,” Proc. of IEEE International Conference on Intelligent Robots and Systems, pp. 529–536, 2016.\nA. Jafari, N. Tsagarakis, and D. Caldwell, “Energy efficient actuators with adjustable stiffness: A review on AwAS, AwAS-II and CompACT VSA changing stiffness based on lever mechanism,” Industrial Robot: An International Journal, vol. 42, no. 3, pp. 242–251, 2015.\nM. Dezman and A. Gams, “Rotatable cam-based variableratio lever compliant actuator for wearable devices,” Mechanism and Machine Theory, vol. 130, pp. 508–522, 2018.\nJ. Sun, Z. Guo, Y. Zhang, X. Xiao, and J. Tan, “A novel design of serial variable stiffness actuator based on an archimedean spiral relocation mechanism,” IEEE\u002FASME Transactions on Mechatronics, vol. 23, no. 5, pp. 2121–2131, October 2018.\nJ. Sun, Z. Guo, D. Sun, S. He, and X. Xiao, “Design, modeling and control of a novel compact, energy-efficient, and rotational serial variable stiffness actuator (SVSA-II),” Mechanism and Machine Theory, vol. 130, pp. 123–136, 2018.\nT. Exley and A. Jafari, “Maximizing energy efficiency of variable stiffness actuators through an interval-based optimization framework,” Sensors and Actuators A: Physical, vol. 332, 113123, December 2021.\nA. Jafari, N. G. Tsagarakis, I. Sardellitti, and D. G. Caldwell, “A new actuator with adjustable stiffness based on a variable ratio lever mechanism,” IEEE\u002FASME Transactions on Mechatronics, vol. 19, no. 1, pp. 55–63, February 2014.\nS. S. Groothuis, G. Rusticelli, A. Zucchelli, and S. Stramigioli, “The variable stiffness actuator vsaUT-II: Mechanical design, modeling, and identification,” IEEE\u002FASME Transactions on Mechatronics, vol. 19, no. 2, pp. 589–597, 2014.\nW. Roozing, Z. Li, G. A. Medrano-Cerda, D. G. Caldwell, and N. G. Tsagarakis, “Development and control of a compliant asymmetric antagonistic actuator for energy efficient mobility,” IEEE\u002FASME Transactions on Mechatronics, vol. 21, no. 2, pp. 1080–1091, April 2016.\nZ. Y. Li, S. P. Bai, O. Madsen, W. H. Chen, and J. B. Zhang, “Design, modeling and testing of a compact variable stiffness mechanism for exoskeletons,” Mechanism and Machine Theory, vol. 151, 103905, 2020.\nP. Bilancia, G. Berselli, and G. Palli, “Virtual and physical prototyping of a beam-based variable stiffness actuator for safe human-machine interaction,” Robotics and Computer-Integrated Manufacturing, vol. 65, 101886, 2020.\nN.G. Tsagarakis, I. Sardellitti, and D. G. Caldwell, “A new variable stiffness actuator (CompAct-VSA): Design and modeling,” Proc. of IEEE\u002FRSJ International Conference on Intelligent Robots and Systems, IROS, pp. 378–383, 2011.\nG. Buondonno and A. de Luca, “Efficient computation of inverse dynamics and feedback linearization for VSA-based robots,” IEEE Robotics and Automation Letters, vol. 1, no. 2, pp. 908–915, July 2016.\nM. Trumic, K. Jovanovic, and A. Fagiolini, “Decoupled nonlinear adaptive control of position and stiffness for pneumatic soft robots,” The International Journal of Robotics Research, 0278364920903787, 2020.\nF. Petit, A. Daasch, and A. Albu-Schaffer, “Backstepping control of variable stiffness robots,” IEEE Transactions on Control Systems Technology, vol. 23, no. 6, pp. 2195–2202, 2015.\nL. Zhang, Z. Li, and C. Yang, “Adaptive neural network based variable stiffness control of uncertain robotic systems using disturbance observer,” IEEE Transactions on Industrial Electronics, vol. 64, no. 3, pp. 2236–2245, 2017.\nE. Psomopoulou, A. Theodorakopoulos, Z. Doulgeri, and G. A. Rovithakis, “Prescribed performance tracking of a variable stiffness actuated robot,” IEEE Transactions on Control Systems Technology, vol. 23, no. 5, pp. 1914–1926, 2015.\nS. Luo and R. 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Dai, “Improving the rapidity of nonlinear tracking differentiator via feedforward,” IEEE Transactions on Industrial Electronics, vol. 61, no. 7, pp. 3736–3743, July 2014.\nZ. Liu, G. Lai, Y. Zhang, X. Chen, and C. Chen, “Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis,” IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 12, pp. 2129–2140, December 2014.\nX. Chi, S. Quan, J. Chen, Y. Wang, and H. He, “Proton exchange membrane fuel cell-powered bidirectional DC motor control based on adaptive sliding-mode technique with neural network estimation,” International Journal of Hydrogen Energy, vol. 45, no. 39, pp. 20282–20292, 2020.\nZ. Chen, “Nussbaum functions in adaptive control with time-varying unknown control coefficients,” Automatica, vol. 102, pp. 72–79, April 2019.",{"VOID":137},"10.1007\u002Fs12555-021-0629-4","PUBLICATION","VERIFIED","2025-01-06T11:19:02.811+00:00","Auto Verify",[143],"VI","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs12555-021-0629-4",[146,162,175,188,202,216],{"id":147,"sortIndex":23,"researcher":22,"roles":148,"affiliations":150,"properties":159,"displayName":161,"givenName":22,"familyName":22},"3ea2bb90-141f-44b9-aa5d-45fecbdd763a",[149],"AUTHOR",[151],{"id":152,"sortIndex":23,"affiliation":153,"properties":22},"06ebadd3-aadb-47ec-b0b7-8371fbcd4a41",{"id":152,"createTime":22,"updateTime":22,"relativeEntities":154,"slug":22,"properties":155,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":158,"statistic":22},[],{"title":156},{"VI":157},"State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China",[],{"title":160},{"VI":161},"Yu Xia",{"id":163,"sortIndex":92,"researcher":22,"roles":164,"affiliations":165,"properties":172,"displayName":174,"givenName":22,"familyName":22},"b151a16e-4f2f-44ab-ac16-87b0c88a2754",[149],[166],{"id":152,"sortIndex":23,"affiliation":167,"properties":22},{"id":152,"createTime":22,"updateTime":22,"relativeEntities":168,"slug":22,"properties":169,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":171,"statistic":22},[],{"title":170},{"VI":157},[],{"title":173},{"VI":174},"Jun-Yang Li",{"id":176,"sortIndex":91,"researcher":22,"roles":177,"affiliations":178,"properties":185,"displayName":187,"givenName":22,"familyName":22},"90c89705-a937-488a-82d4-e48dad7be0fa",[149],[179],{"id":152,"sortIndex":23,"affiliation":180,"properties":22},{"id":152,"createTime":22,"updateTime":22,"relativeEntities":181,"slug":22,"properties":182,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":184,"statistic":22},[],{"title":183},{"VI":157},[],{"title":186},{"VI":187},"Yan-Kui Song",{"id":189,"sortIndex":190,"researcher":22,"roles":191,"affiliations":192,"properties":199,"displayName":201,"givenName":22,"familyName":22},"517a1f21-3376-4fb0-ac56-dfb85cfb9e8f",3,[149],[193],{"id":152,"sortIndex":23,"affiliation":194,"properties":22},{"id":152,"createTime":22,"updateTime":22,"relativeEntities":195,"slug":22,"properties":196,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":198,"statistic":22},[],{"title":197},{"VI":157},[],{"title":200},{"VI":201},"Jia-Xu Wang",{"id":203,"sortIndex":204,"researcher":22,"roles":205,"affiliations":206,"properties":213,"displayName":215,"givenName":22,"familyName":22},"b5ad73b6-9038-4dc1-8aad-6c35fda854fa",4,[149],[207],{"id":152,"sortIndex":23,"affiliation":208,"properties":22},{"id":152,"createTime":22,"updateTime":22,"relativeEntities":209,"slug":22,"properties":210,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":212,"statistic":22},[],{"title":211},{"VI":157},[],{"title":214},{"VI":215},"Yan-Feng Han",{"id":217,"sortIndex":218,"researcher":22,"roles":219,"affiliations":220,"properties":227,"displayName":229,"givenName":22,"familyName":22},"9a21e6c1-493e-4d93-b525-84c7c6ad4b8d",5,[149],[221],{"id":152,"sortIndex":23,"affiliation":222,"properties":22},{"id":152,"createTime":22,"updateTime":22,"relativeEntities":223,"slug":22,"properties":224,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":226,"statistic":22},[],{"title":225},{"VI":157},[],{"title":228},{"VI":229},"Ke Xiao","ARTICLE",{"url":144,"publisher":232,"properties":278},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":233,"slug":10,"properties":234,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":238,"manageAffiliations":247,"indexDatabases":258,"url":22,"thumbnailPath":22,"statistic":273,"gsStatistic":22,"type":117,"analyzePriority":22},[],{"issn":235,"title":236,"eissn":237},{"VOID":15},{"EN":17},{"VOID":13},[239,243],{"id":26,"createTime":22,"updateTime":22,"relativeEntities":240,"label":241,"description":242,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":29},{},{"id":32,"createTime":22,"updateTime":22,"relativeEntities":244,"label":245,"description":246,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":35},{},[248,253],{"id":39,"createTime":22,"updateTime":22,"relativeEntities":249,"slug":22,"properties":250,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":252,"statistic":22},[],{"title":251},{"EN":43},[],{"id":46,"createTime":22,"updateTime":22,"relativeEntities":254,"slug":22,"properties":255,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":257,"statistic":22},[],{"title":256},{"EN":50},[],[259,266],{"id":54,"indexDatabase":260,"url":67,"indexYears":22,"academicFieldIds":265,"indexDatabaseRanking":22},{"id":56,"createTime":22,"updateTime":22,"relativeEntities":261,"label":262,"description":263,"key":63,"publicationTags":264,"standard":22},[],{"EN":59,"VI":59},{"EN":61,"VI":62},[65,66],[69],{"id":71,"indexDatabase":267,"url":82,"indexYears":83,"academicFieldIds":272,"indexDatabaseRanking":87},{"id":73,"createTime":22,"updateTime":22,"relativeEntities":268,"label":269,"description":270,"key":79,"publicationTags":271,"standard":22},[],{"EN":76,"VI":76},{"EN":76,"VI":78},[81],[85,86],{"impactFactor":23,"impactFactorByYear":274,"i10Index":91,"i10IndexLast5Year":92,"totalPublication":93,"totalPublicationByYear":275,"totalCitation":110,"totalCitationByYear":276,"totalCitationPerPublication":114,"totalCitationPerPublicationByYear":277,"hindexLast5Year":91,"hindex":91},{"2022":90},{"2003":92,"2009":95,"2010":96,"2011":97,"2012":98,"2013":99,"2014":100,"2015":99,"2016":101,"2017":102,"2018":103,"2019":104,"2020":105,"2021":106,"2022":107,"2023":108,"2024":109},{"2003":112,"2020":113},{"2003":112,"2020":116},{"pages":279,"volume":281},{"VOID":280},"975-992",{"VOID":282},"21","2023-02-11",2023,[87,65],false,{"id":288,"createTime":289,"updateTime":290,"relativeEntities":291,"slug":292,"properties":293,"entityType":138,"verifyStatus":139,"verifyTime":303,"verifyNote":141,"languages":22,"translateLanguages":304,"viewCount":23,"primaryUrl":305,"fullTextUrl":22,"authors":306,"publicationType":230,"publisherRelationship":337,"citationCount":22,"citationInfo":22,"publishDate":389,"publishYear":390,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":391,"openAccess":22,"references":22,"isForceReanalyzing":286},"11c97c03-a8ed-4e7f-a9b4-2862e15937d2","2024-01-16T21:45:07.565+00:00","2026-09-08T08:15:22.611+00:00",[],"Switching-networked-attitude-control-of-an-unmanned-quadrotor",{"abstract":294,"title":296,"references":299,"doi":301},{"EN":295},"In this article, a switching networked attitude controller for an unmanned quadrotor over a wireless sensor network is presented. To deal with the network induced time varying delays, the quadrotor is being modeled as a switching time varying linear system, while the applied switching output feedback control scheme, is calculated based on Linear Matrix Inequalities, and is able to guarantee the stability of the quadrotor under arbitrary changes in the time delays.",{"EN":297,"VI":298},"Switching networked attitude control of an unmanned quadrotor","Điều khiển tư thế qua mạng chuyển mạch của quadrotor không người lái",{"VOID":300},"A. Ryan and J. Hedrick, “A mode-switching path planner for UAV-assisted search and rescue,” Proc. of European Control Conference, Seville, Spain, 2005, pp. 1471–1476, 2004.\nP. Doherty and P. Rudol, “A UAV search and rescue scenario with human body detection and geolocalization,” Advances in Artificial Intelligence, vol. 4830, pp. 1–13, 2007.\nL. Merino, F. Caballero, J. Martinez, and A. Ollero, “Cooperative fire detection using unmanned aerial vehicles,” Proc. of IEEE International Conference on Robotics and Automation, Barcelona, Spain, pp. 1884–1889, April 2005.\nK. Alexis, G. Nikolakopoulos, A. Tzes, and L. Dritsas, “Coordination of helicopter (UAVs) for aerial (Forest-Fire) surveillance,” in Applications of Intelligent Control to Engineering Systems, pp. 169–193, Springer, Netherlands, June 2009.\nA. Girard, A. Howell, and J. Hedrick, “Border patrol and surveillance missions using multiple unmanned air vehicles,” Proc. of the 43rd IEEE Conference on Decision and Control, vol. 1, pp. 620–625, December 2004.\nJ. Kim and S. Sukkarieh, “Airborne simultaneous localisation and map building,” Proc. of the IEEE International Conference on Robotics and Automation, vol. 1, pp. 406–411, 2003.\nS. Herwitz, L. Johnson, S. Dunagan, R. Higgins, D. Sullivan, J. Zheng, B. Lobitz, B. Leung, B. Gallmeyer, M. Aoyagi, R. Slye, and J. Brass, “Imaging from an unmanned aerial vehicle: agricultural surveillance and decision support,” Computers and Electronics in Agriculture, vol. 44, no. 1, pp. 49–61, July 2004.\nN. Metni and T. Hamel, “A UAV for bridge inspection: Visual servoing control law with orientation limits,” Automation in Construction, vol. 17, no. 1, pp. 3–10, November 2007.\nS. Gray, “Cooperation between UAVs in search and destroy mission,” American Institute of Aeronautics and Astronautics (AIAA) Guidance, Navigation, and Control Conference and Exhibit, Austin, Texas, 2003.\nS. Leishman, Principles of Helicopter Aerodynamics, 2nd ed., Cambridge University Press, April 2006.\nS. Bouabdallah, M. Becker, and R. Siegwart, “Autonomous miniature flying robots: coming soon! — research, development, and results,” IEEE Robotics & Automation Magazine, vol. 14, no. 3, pp. 88–98, 2007.\nS. Bouabdallah, A. Noth, and R. Siegwart, “PID vs LQ control techniques applied to an indoor micro quadrotor,” Proc. of the IEEE\u002FRSJ International Conference on Intelligent Robots and Systems, Sendai, Japan, pp. 2451–2456, 2004.\nA. Benallegue, A. Mokhtari, and L. Fridman, “Feedback linearization and high order sliding mode observer for a quadrotor UAV,” Proc. of International Workshop on Variable Structure Systems, Alghero, Sardinia, pp. 365–372, 2006.\nS. L. Waslander, G. M. Hoffmann, J. S. Jang, and C. J. Tomlin, “Multi-agent quadrotor testbed control design: Integral sliding mode vs. reinforcement learning,” Proc. of the IEEE\u002FRSJ International Conference on Intelligent Robotics and Systems, Alberta, Canada, pp. 468–473, 2005.\nI. Akyildiz, W. Su, Y. Sankarasubramamian, and E. Cayirci, “Wireless sensor networks: a survey,” Computer Networks, vol. 38, no. 4, pp. 393–422, 2002.\nF. Zhao and L. Guibas, Wireless Sensor Networks, pp. 9–16, Elsevier, 2004.\nC. Buratti, A. Conti, D. Dardari, and R. Verdone, “An overview on wireless sensor networks technology and evolution,” Sensors, vol. 9, pp. 6869–6896, 2009.\nC. Garcia-Hernandez, P. Ibarguengoytia-Gonzalez, and J. Garcia-Hernandez, “Wireless sensor networks and applications: a survey,” Int. J. of Computer Science Network Security, vol. 7, pp. 264–273, 2007.\nS. Bouabdallah and R. Siegwart, “Full control of a quadrotor,” Proc. of IEEE\u002FRSJ International Conference on Intelligent Robots and Systems, pp. 153–158, 2007.\nJ. Escareno, A. Sanchez, O. Garcia, and R. Lozano, “Modeling and global control of the longitudinal dynamics of a coaxial convertible mini-UAV in hover mode,” Journal of Intelligent and Robotic Systems, vol. 54, no. 1, pp. 261–273, March 2009.\nEpson, XFOIL, http:\u002F\u002Fglobal.epson.com\u002Fnewsroom\u002Fnews, 2004.\nF. Bohorquez, F. Rankinsy, J. Baerdez, and D. Pines, “Hover Performance of rotor blades at low Reynolds numbers for rotary wing micro air vehicles. An experimental and CFD study,” AIAA Applied Aerodynamics Conference, Orlando, USA, 2003.\nF. Lian, J. Moyne, and D. Tilbury, “Network design consideration for distributed control systems,” IEEE Trans. on Control Systems Technology, vol. 10, no. 2, pp. 297–307, 2002.\nG. Nikolakopoulos, A. Panousopoulou, A. Tzes, and J. Lygeros, “Multi-hoping induced gain scheduling for wireless networked controlled systems,” Asian Journal of Control, vol. 9, no. 4, pp. 450–457, 2007.\nA. Tzes, G. Nikolakopoulos, and I. Koutroulis, “Development and experimental verification of a mobile client-centric networked controlled system,” European Journal of Control, vol. 11, pp. 1–13, 2005.\nL. Dritsas, G. Nikolakopoulos, and A. Tzes, “Constrained optimal control over networks with uncertain delays,” Proc. of the 45th IEEE Conference on Decision and Control, no. FrA11.4\u002F1384, pp. 4993–49 938, 2003.\nG. Hoffmann, H. Huang, S. Waslander, and C. Tomlin, “Quadrotor helicopter flight dynamics and control: theory and experiment,” Proc. of the AIAA Guidance, Navigation, and Control Conference, 2007.\nS. Bouabdallah, Design and Control of Quadrotors with Application to Autonomous Flying, Ph.D. Dissertation, STI School of Engineering, EPFL, Lausanee, 2007.\nG. Nikolakopoulos, A. Panousopoulou, and A. Tzes, “Experimental controller tuning and QOS optimization of a wireless transmission scheme for real-time remote control applications,” Control Engineering Practice, vol. 16, no. 3, pp. 333–346, March 2008.\nS. Ge, Z. Sun, and T. Lee, “Reachability and controllability of switched linear discrete-time systems,” IEEE Trans. on Automatic Control, vol. 46, no. 9, pp. 1437–1441, September 2001.\nJ. Daafouz, P. Riedinger, and C. Iung, “Stability analysis and control synthesis for switched systems: a switched Lyapunov function approach,” IEEE Trans. on Automatic Control, vol. 47, no. 11, pp. 1883–1887, 2002.\nA. Tayebi and S. McGilvray, “Attitude stabilization of a VTOL quadrotor aircraft,” IEEE Trans. on Control Systems Technology, vol. 14, no. 3, pp. 562–571, 2006.\nK. Alexis, G. Nikolakopoulos, and A. Tzes, “Design and experimental verification of a constrained finite time optimal control scheme for the attitude control of a quadrotor helicopter subject to wind gusts,” Proc. of International Conference on Robotics and Automation, Anchorage, Alaska, USA, pp. 1636–1641, 2010.\nK. Alexis, G. Nikolakopoulos, and A. Tzes, “Constrained optimal attitude control of a quadrotor helicopter subject to wind-gusts: experimental studies,” Proc. of American Control Conference, Baltimore, USA, pp. 4451–4455, 2010.\nK. Alexis, G. Nikolakopoulos, and A. Tzes, “Switching model predictive attitude control for a quadrotor helicopter subject to atmospheric disturbances,” Control Engineering Practice, vol. 19, no. 10, pp. 1195–1207, October 2011.\nK. Alexis, G. Nikolakopoulos, and A. Tzes, “Model predictive attitude control of an unmanned quadrotor helicopter subject to atmospheric disturbances,” Proc. of the IEEE International Symposium on Industrial Electronics, Bari, Italy, 4–7 July 2010.\nM. Drela, “XFOIL,” http:\u002F\u002Fweb.mit.edu\u002Fdrela\u002FPublic\u002Fweb\u002Fxfoil\u002F, 2008.\nP. Pounds, R. Mahony, and P. Corke, “Modelling and control of a quad-rotor robot,” Proc. of the Australasian Conference on Robotics and Automation, Auckland, New Zealand, December 6–8, 2006.",{"VOID":302},"10.1007\u002Fs12555-011-0132-4","2025-02-07T18:29:57.497+00:00",[143],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs12555-011-0132-4",[307,322],{"id":308,"sortIndex":23,"researcher":22,"roles":309,"affiliations":310,"properties":319,"displayName":321,"givenName":22,"familyName":22},"0bf3c253-1756-4816-96ae-08367d996466",[149],[311],{"id":312,"sortIndex":23,"affiliation":313,"properties":22},"3ceb353c-c682-4268-81fa-2c83440eb084",{"id":312,"createTime":22,"updateTime":22,"relativeEntities":314,"slug":22,"properties":315,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":318,"statistic":22},[],{"title":316},{"VI":317},"Department of Computer, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden",[],{"title":320},{"VI":321},"George Nikolakopoulos",{"id":323,"sortIndex":92,"researcher":22,"roles":324,"affiliations":325,"properties":334,"displayName":336,"givenName":22,"familyName":22},"0032ab49-7b6e-4615-8a76-31ce1e6d7f31",[149],[326],{"id":327,"sortIndex":23,"affiliation":328,"properties":22},"62b6d11b-9b79-416b-9535-60bf4a93e979",{"id":327,"createTime":22,"updateTime":22,"relativeEntities":329,"slug":22,"properties":330,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":333,"statistic":22},[],{"title":331},{"VI":332},"Swiss Federal Institute of Technology (ETHZ), ASL, Zuerich, Switzerland",[],{"title":335},{"VI":336},"Kostas Alexis",{"url":305,"publisher":338,"properties":384},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":339,"slug":10,"properties":340,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":344,"manageAffiliations":353,"indexDatabases":364,"url":22,"thumbnailPath":22,"statistic":379,"gsStatistic":22,"type":117,"analyzePriority":22},[],{"issn":341,"title":342,"eissn":343},{"VOID":15},{"EN":17},{"VOID":13},[345,349],{"id":26,"createTime":22,"updateTime":22,"relativeEntities":346,"label":347,"description":348,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":29},{},{"id":32,"createTime":22,"updateTime":22,"relativeEntities":350,"label":351,"description":352,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":35},{},[354,359],{"id":39,"createTime":22,"updateTime":22,"relativeEntities":355,"slug":22,"properties":356,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":358,"statistic":22},[],{"title":357},{"EN":43},[],{"id":46,"createTime":22,"updateTime":22,"relativeEntities":360,"slug":22,"properties":361,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":363,"statistic":22},[],{"title":362},{"EN":50},[],[365,372],{"id":54,"indexDatabase":366,"url":67,"indexYears":22,"academicFieldIds":371,"indexDatabaseRanking":22},{"id":56,"createTime":22,"updateTime":22,"relativeEntities":367,"label":368,"description":369,"key":63,"publicationTags":370,"standard":22},[],{"EN":59,"VI":59},{"EN":61,"VI":62},[65,66],[69],{"id":71,"indexDatabase":373,"url":82,"indexYears":83,"academicFieldIds":378,"indexDatabaseRanking":87},{"id":73,"createTime":22,"updateTime":22,"relativeEntities":374,"label":375,"description":376,"key":79,"publicationTags":377,"standard":22},[],{"EN":76,"VI":76},{"EN":76,"VI":78},[81],[85,86],{"impactFactor":23,"impactFactorByYear":380,"i10Index":91,"i10IndexLast5Year":92,"totalPublication":93,"totalPublicationByYear":381,"totalCitation":110,"totalCitationByYear":382,"totalCitationPerPublication":114,"totalCitationPerPublicationByYear":383,"hindexLast5Year":91,"hindex":91},{"2022":90},{"2003":92,"2009":95,"2010":96,"2011":97,"2012":98,"2013":99,"2014":100,"2015":99,"2016":101,"2017":102,"2018":103,"2019":104,"2020":105,"2021":106,"2022":107,"2023":108,"2024":109},{"2003":112,"2020":113},{"2003":112,"2020":116},{"pages":385,"volume":387},{"VOID":386},"389-397",{"VOID":388},"11","2013-03-27",2013,[87,65],{"id":393,"createTime":394,"updateTime":395,"relativeEntities":396,"slug":397,"properties":398,"entityType":138,"verifyStatus":139,"verifyTime":408,"verifyNote":141,"languages":22,"translateLanguages":409,"viewCount":23,"primaryUrl":410,"fullTextUrl":22,"authors":411,"publicationType":230,"publisherRelationship":457,"citationCount":22,"citationInfo":22,"publishDate":508,"publishYear":284,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":509,"openAccess":22,"references":22,"isForceReanalyzing":286},"50004691-fe9b-4019-8809-bc7616e6bf28","2024-01-18T00:11:22.652+00:00","2026-09-06T11:11:26.776+00:00",[],"On-line-Deadlock-free-Planning-of-N-industrial-robot-Arms-With-Independent-Controllers-Using-Advanced-Escaping-Method",{"abstract":399,"title":401,"references":404,"doi":406},{"EN":400},"This work presents an on-line deadlock avoidance system for N-industrial-robot arms utilizing an advanced escaping method. Robots within the same workspace are controlled via independent controllers using point-to-point commands. Besides, the robots have no preceding information about the commands that will be sent to the controllers after starting the system of robots up. In practice, the deadlock situations, in which the robot becomes an obstacle in front of another in the collision avoidance process, are an industrially common problem in on-line planning. Therefore, to make the proposed on-line collision avoidance system more functional in industrial applications, a deadlock avoidance method is integrated into the system. We have previously proposed a simple escaping method to avoid the deadlocks among the end-effectors of two robots, thereafter, an escaping method for the whole bodies of two robots has been proposed. In this work, an advanced escaping method using our previously devised advanced collision map is developed to avoid the deadlocks of N-industrial-robot arms. The advanced collision map has been designed to detect potential collisions between all body parts of robots and to represent collisions as collision areas on the map. The map is created for the robot that has acquired the command and is going to execute it and other robots in the workspace. Thus, the robot treats other robots as either static or dynamic obstacles. Hence, for generating a collision-free trajectory of the robots, time scheduling of command execution time is applied to avoid any collision areas on the map. The effectiveness of the proposed collision and deadlock avoidance system is demonstrated by testing the system on an OpenGL-based simulator. In addition, the system is evaluated by analyzing the results of many simulations with different robot arrangement patterns in the workspace as well as by comparing the system with the most relevant work to this article.",{"EN":402,"VI":403},"On-line Deadlock-free Planning of N-industrial-robot Arms With Independent Controllers Using Advanced Escaping Method","Lập kế hoạch trực tuyến tránh bế tắc cho N cánh tay robot công nghiệp có các bộ điều khiển độc lập sử dụng phương pháp thoát tiên tiến",{"VOID":405},"B. H. Lee and C. S. G. Lee, “Collision-free motion planning of two robots,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 17, pp. 21–32, January 1987.\nZ. Bien and J. Lee, “A minimum-time trajectory planning method for two robots,” IEEE Transactions on Robotics and Automation, vol. 8, pp. 414–418, June 1992.\nC. Chang, M. J. Chung, and B. H. Lee, “Collision avoidance of two general robot manipulators by minimum delay time,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 24, pp. 517–522, March 1994.\nF. Schwarzer, M. Saha, and J.-C. Latombe, “Adaptive dynamic collision checking for single and multiple articulated robots in complex environments,” IEEE Transactions on Robotics, vol. 21, pp. 338–353, June 2005.\nN. Asakawa and Y. Kanjo, “Collision avoidance of a welding robot for a large structure(application of potential field),” International Journal of Automation Technology, vol. 7, no. 2, pp. 190–195, 2013.\nE. Freund and H. Hoyer, “Pathfinding in multi-robot systems: Solution and applications,” Proc. IEEE IEEE International Conference on Robotics and Automation (ICRA), vol. 3, pp. 103–111, April 1986.\nR. Z. Lise Cellier, Pierre Dauchez and M. Uchiyama, “Collision avoidance for a two-arm robot by reflex actions: Simulations and experimentations,” Journal of Intelligent & Robotic Systems, vol. 2, no. 14, pp. 219–238, 1995.\nK.-S. Hwang, M.-Y. Ju, and Y.-J. Chen, “Speed alteration strategy for multijoint robots in co-working environment,” IEEE Transactions on Industrial Electronics, vol. 50, pp. 385–393, April 2003.\nP. Bosscher, D. Hendman, H. Corporation, and P. Bay, “Real-time collision avoidance algorithm for robotic manipulators,” Proc. IEEE International Conference on Technologies for Practical Robot Applications, pp. 113–122, November 2009.\nY. Liu, C. Yu, C. Sheng, and T. Zhang, “Self-collision avoidance trajectory planning and robust control of a dualarm space robot,” International Journal of Control, Automation, and Systems, vol. 16, no. 6, pp. 2896–2905, 2018.\nH. J. Yoon, S. Y. Chung, and M. J. Hwang, “Shadow space modeling and task planning for collision-free cooperation of dual manipulators for planar task,” International Journal of Control, Automation, and Systems, vol. 17, no. 4, pp. 995–1006, 2019.\nA. M. Salmaninejad, S. Zilles, and R. V. Mayorga, “Motion path planning of two robot arms in a common workspace,” Proc. of IEEE International Conference on Systems, Man and Cybernetics, pp. 45–51, October 2020.\nL. An and G.-H. Yang, “Collisions-free distributed optimal coordination for multiple euler-lagrangian systems,” IEEE Transactions on Automatic Control, vol. 67, pp. 460–467, January 2022.\nL. Zhang and G.-H. Yang, “Secure adaptive trajectory tracking control for nonlinear robot systems under multiple dynamic obstacles: Safety barrier certificates,” IEEE Transactions on Industrial Electronics, vol. 69, pp. 11549–11559, Novebmer 2022.\nP. A. Donnell and T. Lozano-Periz, “Deadlock-free and collision-free coordination of two robot manipulators,” Proc. of IEEE International Conference on Robotics and Automation (ICRA), vol. 1, pp. 484–489, 14–19 May 1989.\nX. Cheng, “On-line collision-free path planning for service and assembly tasks by a two-arm robot,” Proc. IEEE International Conference on Robotics and Automation (ICRA), vol. 2, pp. 1523–1528, 21–27 May 1995.\nM. Mediavilla, J.-C. Fraile, and I. J. Galindo, “Selection of strategies for collision-free motion in multi-manipulator systems,” Journal of Intelligent & Robotic Systems, vol. 38, pp. 85–104, September 2003.\nN. Gafur, G. Kanagalingam, A. Wagner, and M. Ruskowski, “Dynamic collision and deadlock avoidance for multiple robotic manipulators,” IEEE Access, vol. 10, pp. 55766–55781, May 2022.\nA. Y. Afaghani and Y. Aiyama, “On-line collision avoidance between two robot manipulators using collision map and simple escaping method,” Proc. of IEEE\u002FSICE International Symposium on System Integration, pp. 105–110, December 2013.\nA. Y. Afaghani and Y. Aiyama, “On-line collision-free motion of two command-based industrial manipulators (cooperation control of multi robots),” Proc. of JSME Conference on Robotics and Mechatronics (Robomech), no. 12–2, pp. 2A1-W03(1–4), 25–29 May 2014.\nTechnology Transfer Service, “Integrated robotic process solutions for manufacturing.” https:\u002F\u002Fwww.techtransfer.com\u002Fblog\u002Fintegrated-robotic-process-solutions-for-manufacturing\u002F, 2023. Accessed: 2023-04-25.\nDirect Industry, “Robot controller irc5.” http:\u002F\u002Fwww.directindustry.com\u002Fprod\u002Fabb-robotics\u002Fproduct-30265-169114.html, 2023. Accessed: 2023-04-25.\nA. Y. Afaghani and Y. Aiyama, “On-line collision avoidance of two command-based industrial robotic arms using advanced collision map,” International Journal of Robotics and Mechatronics (JRM), vol. 26, pp. 321–330, June 2014.\nJ. Zhou, K. Nagase, S. Kimura, and Y. Aiyama, “Collision avoidance of two manipulators using rt-middleware,” Proc. of IEEE\u002FSICE International Symposium on System Integration, pp. 1031–1036, December 2011.\nJ. Zhou and Y. Aiyama, “On-line collision avoidance system for two PTP command-based manipulators with distributed controller,” International Journal of Advanced Robotic Systems, vol. 29, no. 4, pp. 239–251, 2015.\nA. Y. Afaghani, On-line Collision and Deadlock Avoidance of PTP Command-Based Industrial Manipulators using Advanced Collision Map, Ph.D. Dissertation, Graduate School of System and Information Engineering, University of Tsukuba, 2015.\nM. Perez-Francisco, A. P. del Pobil, and B. Martinez, “Fast collision detection for realistic multiple moving robots,” Proc. of IEEE International Conference on Advanced Robotics (ICAR), pp. 187–192, 7–9 Jul 1997.\nG. Bradshaw, Bounding Volume Hierarchies for Level-of-Detail Collision Handling, Ph.D. Dissertation, Trinity College, University of Dublin, 2002.\nB. Mirtich, “V-clip: Fast and robust polyhedral collision detection,” ACM Transactions on Graphics, vol. 17, no. 3, pp. 177–208, 1998.\nS. Gottschalk, Collision Queries Using Oriented Bounding Boxes, Ph.D. Dissertation, Department of Computer Science, University of North Carolina, 2000.\nJ. Klosowski, Efficient Collision Detection for Interactive 3D Graphics and Virtual Environments, Ph.D. Dissertation, State University of New York, 1998.\nM. C. L. E. Larsen, S. Gottschalk and D. Manocha, “Fast proximity queries with swept sphere volumes,” Techical Report, Department of Computer Sciences, UNC Chapel Hill, 1999.\nA. Y. Afaghani and Y. Aiyama, “On-line collision detection of n-robot industrial manipulators using advanced collision map,” Proc. of International Conference on Advanced Robotics (ICAR), pp. 422–427, July 2015.",{"VOID":407},"10.1007\u002Fs12555-022-1051-2","2024-10-11T05:29:52.805+00:00",[143],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs12555-022-1051-2",[412,427,442],{"id":413,"sortIndex":23,"researcher":22,"roles":414,"affiliations":415,"properties":424,"displayName":426,"givenName":22,"familyName":22},"c1989fa3-84e7-49ba-bfb7-478ca37ecd23",[149],[416],{"id":417,"sortIndex":23,"affiliation":418,"properties":22},"4053cc21-01aa-4c90-90c0-bfa34c00fb62",{"id":417,"createTime":22,"updateTime":22,"relativeEntities":419,"slug":22,"properties":420,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":423,"statistic":22},[],{"title":421},{"VI":422},"School of Mechatronics Engineering, KTO Karatay University, Karatay, Konya, Turkey",[],{"title":425},{"VI":426},"Ahmad Yasser Afaghani",{"id":428,"sortIndex":92,"researcher":22,"roles":429,"affiliations":430,"properties":439,"displayName":441,"givenName":22,"familyName":22},"d7020046-cc4d-4735-afa8-00f8ef7bc963",[149],[431],{"id":432,"sortIndex":23,"affiliation":433,"properties":22},"3cf0d57e-16d3-4499-a564-fe8abbc5b28a",{"id":432,"createTime":22,"updateTime":22,"relativeEntities":434,"slug":22,"properties":435,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":438,"statistic":22},[],{"title":436},{"VI":437},"School of Mechanical Department, MYO, Mardin Artuklu University, Mardin, Turkey",[],{"title":440},{"VI":441},"Jamal Eldeen Afaghani",{"id":443,"sortIndex":91,"researcher":22,"roles":444,"affiliations":445,"properties":454,"displayName":456,"givenName":22,"familyName":22},"28332a90-27ad-43d8-9ebc-ca51633ba982",[149],[446],{"id":447,"sortIndex":23,"affiliation":448,"properties":22},"5fdebe8d-e114-47a5-a931-2a0a199753bc",{"id":447,"createTime":22,"updateTime":22,"relativeEntities":449,"slug":22,"properties":450,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":453,"statistic":22},[],{"title":451},{"VI":452},"School of Manipulation System Laboratory, Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan",[],{"title":455},{"VI":456},"Yasumichi Aiyama",{"url":410,"publisher":458,"properties":504},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":459,"slug":10,"properties":460,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":464,"manageAffiliations":473,"indexDatabases":484,"url":22,"thumbnailPath":22,"statistic":499,"gsStatistic":22,"type":117,"analyzePriority":22},[],{"issn":461,"title":462,"eissn":463},{"VOID":15},{"EN":17},{"VOID":13},[465,469],{"id":26,"createTime":22,"updateTime":22,"relativeEntities":466,"label":467,"description":468,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":29},{},{"id":32,"createTime":22,"updateTime":22,"relativeEntities":470,"label":471,"description":472,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":35},{},[474,479],{"id":39,"createTime":22,"updateTime":22,"relativeEntities":475,"slug":22,"properties":476,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":478,"statistic":22},[],{"title":477},{"EN":43},[],{"id":46,"createTime":22,"updateTime":22,"relativeEntities":480,"slug":22,"properties":481,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":483,"statistic":22},[],{"title":482},{"EN":50},[],[485,492],{"id":54,"indexDatabase":486,"url":67,"indexYears":22,"academicFieldIds":491,"indexDatabaseRanking":22},{"id":56,"createTime":22,"updateTime":22,"relativeEntities":487,"label":488,"description":489,"key":63,"publicationTags":490,"standard":22},[],{"EN":59,"VI":59},{"EN":61,"VI":62},[65,66],[69],{"id":71,"indexDatabase":493,"url":82,"indexYears":83,"academicFieldIds":498,"indexDatabaseRanking":87},{"id":73,"createTime":22,"updateTime":22,"relativeEntities":494,"label":495,"description":496,"key":79,"publicationTags":497,"standard":22},[],{"EN":76,"VI":76},{"EN":76,"VI":78},[81],[85,86],{"impactFactor":23,"impactFactorByYear":500,"i10Index":91,"i10IndexLast5Year":92,"totalPublication":93,"totalPublicationByYear":501,"totalCitation":110,"totalCitationByYear":502,"totalCitationPerPublication":114,"totalCitationPerPublicationByYear":503,"hindexLast5Year":91,"hindex":91},{"2022":90},{"2003":92,"2009":95,"2010":96,"2011":97,"2012":98,"2013":99,"2014":100,"2015":99,"2016":101,"2017":102,"2018":103,"2019":104,"2020":105,"2021":106,"2022":107,"2023":108,"2024":109},{"2003":112,"2020":113},{"2003":112,"2020":116},{"pages":505,"volume":507},{"VOID":506},"3696-3711",{"VOID":282},"2023-08-25",[87,65],{"id":511,"createTime":512,"updateTime":513,"relativeEntities":514,"slug":515,"properties":516,"entityType":138,"verifyStatus":139,"verifyTime":526,"verifyNote":141,"languages":22,"translateLanguages":527,"viewCount":23,"primaryUrl":528,"fullTextUrl":22,"authors":529,"publicationType":230,"publisherRelationship":571,"citationCount":22,"citationInfo":22,"publishDate":623,"publishYear":624,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":625,"openAccess":22,"references":22,"isForceReanalyzing":286},"11ce68c4-86b2-46eb-853d-56bf19c15cb4","2024-01-12T01:14:34.297+00:00","2026-09-05T11:26:58.580+00:00",[],"A-Model-Predictive-Control-MPC-Approach-on-Unit-Quaternion-Orientation-Based-Quadrotor-for-Trajectory-Tracking",{"abstract":517,"title":519,"references":522,"doi":524},{"EN":518},"The objective of this paper is to introduce with a quaternion orientation based quadrotor that can be controlled by Model Predictive Control (MPC). As MPC offers promising performance in different industrial applications, quadrotor can be another suitable platform for the application of MPC. The present study consistently adopts unit quaternion approach for quadrotor orientation in order to avoid any axes overlapping problem, widely known as singularity problem whereas Euler angle orientation approach is unable to resolve so. MPC works based on the minimal cost function that includes the attitude error and consequently, the cost function requires quaternion error in order to proceed with process of MPC. Therefore, the main contribution of this study is to introduce a newly developed cost function for MPC because by definition, quaternion error is remarkably different from the attitude error of Euler angle. As a result, a unit quaternion based quadrotor with MPC can ascertain a smooth singularity-free flight that is influenced by model uncertainty. MATLAB and Simulink environment has been used to validate the cost function for quaternion by simulating several trajectories.",{"EN":520,"VI":521},"A Model Predictive Control (MPC) Approach on Unit Quaternion Orientation Based Quadrotor for Trajectory Tracking","Phương pháp điều khiển dự báo theo mô hình (MPC) cho quadrotor dựa trên định hướng quaternion đơn vị nhằm bám quỹ đạo",{"VOID":523},"P. Foehn and D. Scaramuzza, “Onboard state dependent LQR for Agile Quadrotors,” Proc. of IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 6566–6572, 2018.\nE. Hernandez-Martinez, G. Fernandez-Anaya, E. Ferreira, J. Flores-Godoy, and A. Lopez-Gonzalez, “Trajectory tracking of a quadcopter UAV with optimal translational control,” IFAC-PapersOnLine, vol. 48, no. 19, pp. 226–231, 2015.\nA. K. Shastry, M. T. Bhargavapuri, M. Kothari, and S. R. Sahoo, “Quaternion based adaptive control for package delivery using variable-pitch quadrotors,” Proc. of Indian Control Conference (ICC), IEEE, pp. 340–345, 2018.\nX. Zhang, X. Li, K. Wang, and Y. Lu, “A survey of modelling and identification of quadrotor robot,” Abstract and Applied Analysis, vol. 2014, Article ID 320526, 16 pages, 2014.\nH. Parwana, J. S. Patrikar, and M. Kothari, “A novel fully quaternion based nonlinear attitude and position controller,” Proc. of AIAA Guidance, Navigation, and Control Conference, p. 1587, 2018.\nS. Swarnkar, H. Parwana, M. Kothari, and A. Abhishek, “Biplane-quadrotor tail-sitter UAV: flight dynamics and control,” Journal of Guidance, Control, and Dynamics, vol. 41, no. 5, pp. 1049–1067, 2018.\nE. Fresk and G. Nikolakopoulos, “Full quaternion based attitude control for a quadrotor,” Proc. of European Control Conference (ECC), IEEE, pp. 3864–3869, 2013.\nF. Kendoul, “Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems,” Journal of Field Robotics, vol. 29, no. 2, pp. 315–378, 2012.\nM. Islam, M. Okasha, and M. M. Idres, “Trajectory tracking in quadrotor platform by using PD controller and LQR control approach,” IOP Conference Series: Materials Science and Engineering, vol. 260, no. 1, p. 012026, 2017.\nC. J. Ostafew, Learning-based Control for Autonomous Mobile Robots, Doctor of Philosophy, University of Toronto, Canada, 2016.\nA. Kehlenbeck, Quaternion-based Control for Aggressive Trajectory Tracking with a Micro-quadrotor UAV, University of Maryland, College Park, 2014.\nE. Reyes-Valeria, R. Enriquez-Caldera, S. Camacho-Lara, and J. Guichard, “LQR control for a quadrotor using unit quaternions: Modeling and simulation,” Proc. of International Conference on Electronics, Communications and Computing (CONIELECOMP), IEEE, pp. 172–178, 2013.\nK. Djamel, M. Abdellah, and A. Benallegue, “Attitude optimal backstepping controller based quaternion for a uav,” Mathematical Problems in Engineering, vol. 2016, 2016.\nC. Zha, X. Ding, Y. Yu, and X. Wang, “Quaternion-based nonlinear trajectory tracking control of a quadrotor unmanned aerial vehicle,” Chinese Journal of Mechanical Engineering, vol. 30, no. 1, pp. 77–92, 2017.\nT.-T. Tran and C. Ha, “Self-tuning proportional double derivative-like neural network controller for a quadrotor,” International Journal of Aeronautical and Space Sciences, vol. 19, no. 4, pp. 976–985, 2018.\nC. Liu, H. Lu, and W.-H. Chen, “An explicit MPC for quadrotor trajectory tracking,” Proc. of the 34th Chinese Control Conference (CCC), IEEE, pp. 4055–4060, 2015.\nW. Zhao and T. H. Go, “Quadcopter formation flight control combining MPC and robust feedback linearization,” Journal of the Franklin Institute, vol. 351, no. 3, pp. 1335–1355, 2014.\nM. Bangura and R. Mahony, “Real-time model predictive control for quadrotors,” IFAC Proceedings Volumes, vol. 47, no. 3, pp. 11773–11780, 2014.\nM. Chipofya, D. J. Lee, and K. T. Chong, “Trajectory tracking and stabilization of a quadrotor using model predictive control of Laguerre functions,” Abstract and Applied Analysis, vol. 2015, Article ID 916864, 11 pages, 2015.\nK. Alexis, G. Nikolakopoulos, and A. Tzes, “On trajectory tracking model predictive control of an unmanned quadrotor helicopter subject to aerodynamic disturbances,” Asian Journal of Control, vol. 16, no. 1, pp. 209–224, 2014.\nM. Islam, M. Okasha, and M. Idres, “Dynamics and control of quadcopter using linear model predictive control approach,” IOP Conference Series: Materials Science and Engineering, vol. 270, no. 1, p. 012007, 2017.\nT. Zhang, G. Kahn, S. Levine, and P. Abbeel, “Learning deep control policies for autonomous aerial vehicles with mpc-guided policy search,” Proc. of IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 528–535, 2016.\nC. Kanellakis, S. S. Mansouri, and G. Nikolakopoulos, “Dynamic visual sensing based on MPC controlled UAVs,” Proc. of the 25th Mediterranean Conference on Control and Automation (MED), IEEE, pp. 1201–1206, 2017.\nT. Engelhardt, T. Konrad, B. Schäfer, and D. Abel, “Flatness-based control for a quadrotor camera helicopter using model predictive control trajectory generation,” Proc. of the 24th Mediterranean Conference on Control and Automation (MED), IEEE, pp. 852–859, 2016.\nA. Chovancová, T. Fico, P. Hubinský, and F. Duchonˇ, “Comparison of various quaternion-based control methods applied to quadrotor with disturbance observer and position estimator,” Robotics and Autonomous Systems, vol. 79, pp. 87–98, 2016.\nJ.-F. Guerrero-Castellanos, J. J. Téllez-Guzmán, S. Durand, N. Marchand, J. Alvarez-Muñoz, and V. R. Gonzalez-Diaz, “Attitude stabilization of a quadrotor by means of event-triggered nonlinear control,” Journal of Intelligent & Robotic Systems, vol. 73, no. 1–4, pp. 123–135, 2014.\nA. Sudbery, “Quaternionic analysis,” Mathematical Proceedings of the Cambridge Philosophical Society, vol. 85, no. 2, pp. 199–225, Cambridge University Press, 1979.\nJ. Diebel, “Representing attitude: Euler angles, unit quaternions, and rotation vectors,” Matrix, vol. 58, no. 15–16, pp. 1–35, 2006.\nA. Chovancová, T. Fico, L’. Chovanec, and P. Hubinsk, “Mathematical modelling and parameter identification of quadrotor (a survey),” Procedia Engineering, vol. 96, pp. 172–181, 2014.\nS. Lindblom and A. Lundmark, Modelling and Control of a Hexarotor UAV, Linköpings universitet, 2015.\nJ.-L. Blanco, “A tutorial on se (3) transformation parameterizations and on-manifold optimization,” University of Malaga, Tech. Rep, vol. 3, 2010.\nS. Bouabdallah, “Design and control of quadrotors with application to autonomous flying,” 2007.\nJ. Zhang, X. Cheng, and J. Zhu, “Control of a laboratory 3-DOF helicopter: Explicit model predictive approach,” International Journal of Control, Automation and Systems, vol. 14, no. 2, pp. 389–399, 2016.\nM. H. Murillo, A. C. Limache, P. S. R. Fredini, and L. L. Giovanini, “Generalized nonlinear optimal predictive control using iterative state-space trajectories: Applications to autonomous flight of UAVs,” International Journal of Control, Automation and Systems, vol. 13, no. 2, pp. 361–370, 2015.\nA.-W. A. Saif, A. Aliyu, M. Al Dhaifallah, and M. Elshafei, “Decentralized Backstepping Control of a Quadrotor with Tilted-rotor under Wind Gusts,” International Journal of Control, Automation and Systems, vol. 16, no. 5, pp. 2458–2472, 2018.\nMathworks, QP Solver, 2018. Available: https:\u002F\u002Fwww.mathworks.com\u002Fhelp\u002Fmpc\u002Fug\u002Fqp-solver.html\nI. Kugelberg, Black-box Modeling and Attitude Control of a Quadcopter, Master of Science Thesis, Linköping University, 2016.\nY. Wang, A. Ramirez-Jaime, F. Xu, and V. Puig, “Nonlinear model predictive control with constraint satisfactions for a quadcopter,” Journal of Physics: Conference Series, vol. 783, no. 1, p. 012025, 2017.\nW. Zhu, H. Du, Y. Cheng, and Z. Chu, “Hovering control for quadrotor aircraft based on finite-time control algorithm,” Nonlinear Dynamics, vol. 88, no. 4, pp. 2359–2369, 2017.\nL. V. Santana, A. S. Brandão, and M. Sarcinelli-Filho, “Navigation and cooperative control using the ar. drone quadrotor,” Journal of Intelligent & Robotic Systems, vol. 84, no. 1–4, pp. 327–350, 2016.",{"VOID":525},"10.1007\u002Fs12555-018-0860-9","2024-12-08T22:57:42.089+00:00",[143],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs12555-018-0860-9",[530,545,558],{"id":531,"sortIndex":23,"researcher":22,"roles":532,"affiliations":533,"properties":542,"displayName":544,"givenName":22,"familyName":22},"c5ac227e-f141-48b2-8ebc-4e1325b6b990",[149],[534],{"id":535,"sortIndex":23,"affiliation":536,"properties":22},"b33df6d9-05fa-4f51-92c9-3fbf92edd352",{"id":535,"createTime":22,"updateTime":22,"relativeEntities":537,"slug":22,"properties":538,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":541,"statistic":22},[],{"title":539},{"VI":540},"Department of Mechanical Engineering, International Islamic University Malaysia, Kuala Lumpur, Malaysia",[],{"title":543},{"VI":544},"Maidul Islam",{"id":546,"sortIndex":92,"researcher":22,"roles":547,"affiliations":548,"properties":555,"displayName":557,"givenName":22,"familyName":22},"5840efd0-7b83-4186-acbc-3910eb3bd56f",[149],[549],{"id":535,"sortIndex":23,"affiliation":550,"properties":22},{"id":535,"createTime":22,"updateTime":22,"relativeEntities":551,"slug":22,"properties":552,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":554,"statistic":22},[],{"title":553},{"VI":540},[],{"title":556},{"VI":557},"Mohamed 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one of the long-term challenges faced by the International Maritime Organization (IMO), the global navigation satellite system (GNSS) has become increasingly complicated with the rapid development of intelligent ships and autonomous navigation ships. GNSS vulnerability is an important factor affecting navigation safety. Therefore, we propose a multisource position, navigation and time (PNT) data fusion algorithm based on the study of multisource shipborne PNT system model. This algorithm uses the variance genetic model to estimate the measurement variance of a PNT source at the subsequent time step to obtain an estimated value that is close to the real value, thus producing an optimal fusion factor for each PNT source and obtaining highly reliable and high-precision PNT fusion data. The simulation and measurement results show that the multisource PNT fusion algorithm based on the variance genetic model can provide superior reliability and precision when the PNT source is disturbed by abnormal interference.",{"EN":636},"A Multisource PNT Fusion Algorithm Based on a Variance Genetic 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H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, 2nd edition, Morgan Kaufmann, San Francisco, 2005.",{},{"id":22,"text":1039,"url":22,"identifiers":1040},"K. G. Woo, J. H. Lee, M. H. Kim, and Y. J. Lee, “FINDIT: a fast and intelligent subspace clustering algorithm using dimension voting,” Information and Software Technology, vol. 46, pp. 255–271, 2004.",{"doi":1041},"10.1016\u002Fj.infsof.2003.07.003",{"id":22,"text":1043,"url":22,"identifiers":1044},"S. H. Liao and C. H. Wen, “Artificial neural networks classification and clustering of methodologies and applications-literature analysis from 1995 to 2005,” Expert Systems with Applications, vol. 32, pp. 1–11, 2007.",{"doi":1045},"10.1016\u002Fj.eswa.2005.11.014",{"id":22,"text":1047,"url":22,"identifiers":1048},"J. T. Kuo, M. H. Hsieh, W. S. Lung, and N. She, “Using artificial neural network for reservoir eutrophication prediction,” Ecological Modelling, vol. 200, pp. 171–177, 2007.",{"doi":1049},"10.1016\u002Fj.ecolmodel.2006.06.018",{"id":22,"text":1051,"url":22,"identifiers":1052},"R. Setiono and J. Y. L. Thong, “An approach to generate rules from neural networks for regression problems,” European Journal of Operational Research, vol. 155, no. 1, pp. 239–250, 2004.",{"doi":1053},"10.1016\u002FS0377-2217(02)00792-0",{"id":22,"text":1055,"url":22,"identifiers":1056},"L. A. Zadeh, “Fuzzy sets and information granularity,” in Advances in Fuzzy Set Theory and Application, M. Gupta, R. Yager, eds., pp. 3–18, 1979.",{},{"id":22,"text":1058,"url":22,"identifiers":1059},"W. Pedrycz and A. V. Vasilakos, “Linguistic models and linguistic modeling,” IEEE Trans. on Systems, Man, and Cybernetics, Part B, vol. 29, pp. 745–757, 1999.",{"doi":1060},"10.1109\u002F3477.809029",{"id":22,"text":1062,"url":22,"identifiers":1063},"W. Pedrycz and K. C. Kwak, “Linguistic models as a framework of user-centric system modeling,” IEEE Trans. on Systems, Man, and Cybernetics, Part A, vol. 36, pp. 727–745, 2006.",{"doi":1064},"10.1109\u002FTSMCA.2005.855755",{"id":22,"text":1066,"url":22,"identifiers":1067},"W. Pedrycz, “Conditional fuzzy c-means,” Pattern Recognition Letters, vol. 17, pp. 625–631, 1996.",{"doi":1068},"10.1016\u002F0167-8655(96)00027-X",{"id":22,"text":1070,"url":22,"identifiers":1071},"W. Pedrycz and K. C. Kwak, “The development of incremental models,” IEEE Trans. on Fuzzy Systems, vol. 15, pp. 507–518, 2007.",{"doi":1072},"10.1109\u002FTFUZZ.2006.889967",{"id":22,"text":1074,"url":22,"identifiers":1075},"W. Pedrycz, “Conditional fuzzy clustering in the design of radial basis function neural networks,” IEEE Trans. on Neural Networks, vol. 9, pp. 601–612, 1998.",{"doi":1076},"10.1109\u002F72.701174",{"id":22,"text":1078,"url":22,"identifiers":1079},"K. C. Kwak, W. Pedrycz, and M. G. Chun, “Modeling nonlinear systems: an approach of boosted linguistic models,” Lecture Notes in Computer Science, vol. 3614, pp. 514–523, 2005.",{"doi":1080},"10.1007\u002F11540007_62",{"id":22,"text":1082,"url":22,"identifiers":1083},"M. G. Chun, K. C. Kwak, J. W. Ryu, and W. Pedrycz, “A fuzzy rule extraction method for ANFIS using CFCM and fuzzy equalization,” Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 4, pp. 355–361, 2000.",{"doi":1084},"10.20965\u002Fjaciii.2000.p0355",{"id":22,"text":1086,"url":22,"identifiers":1087},"W. Pedrycz, “Fuzzy equalization in the construction of fuzzy sets,” Fuzzy Sets and Systems, vol. 119, pp. 329–336, 2001.",{"doi":1088},"10.1016\u002FS0165-0114(99)00135-9",{"id":22,"text":1090,"url":22,"identifiers":1091},"L. A. Zadeh, “Probability measures of fuzzy events,” Journal of Mathematical Analysis and Applications, vol. 23, no. 2, pp. 421–427, 1968.",{"doi":1092},"10.1016\u002F0022-247X(68)90078-4",{"id":1094,"createTime":1095,"updateTime":1096,"relativeEntities":1097,"slug":1098,"properties":1099,"entityType":138,"verifyStatus":139,"verifyTime":1109,"verifyNote":141,"languages":22,"translateLanguages":22,"viewCount":23,"primaryUrl":1110,"fullTextUrl":22,"authors":1111,"publicationType":230,"publisherRelationship":1170,"citationCount":22,"citationInfo":22,"publishDate":1222,"publishYear":624,"citationAnalyzeStatus":1031,"lastCitationAnalyze":1223,"indexDatabases":1224,"openAccess":22,"references":22,"isForceReanalyzing":286},"515b3243-3b83-4c2f-8172-b98ecbfeaafd","2023-12-09T09:53:00.791+00:00","2026-08-15T22:21:01.494+00:00",[],"Standoff-Tracking-of-a-Moving-Target-for-Quadrotor-Using-Lyapunov-Potential-Function",{"abstract":1100,"title":1102,"gsPaper":1104,"references":1105,"doi":1107},{"EN":1101},"This paper presents a control scheme for standoff tracking of a ground moving target by a quadrotor unmanned aerial vehicle (UAV). The control system is decoupled into outer loop for position control and inner loop for attitude regulation. In the outer loop design, the standoff motion of the vehicle is described in a cylindrical coordinate system attached to the target. After that, the standoff tracking guidance law is designed based on a Lyapunov potential function which can guarantee the stability of the movement. The acceleration signals are produced from the proposed guidance law, and converted to Euler angle commands for the inner control system. A integral backstepping controller is developed to stabilize the attitude of the quadrotor. In particular, the disturbance observer technique is used to deal with the correction terms that account for a non-uniform moving target and constant wind. Numerical simulations are performed to verify the feasibility and performance of the proposed control scheme.",{"EN":1103},"Standoff Tracking of a Moving Target for Quadrotor Using Lyapunov Potential Function",{"VOID":904},{"VOID":1106},"S. Q. Zhu, D. W. Wang, and C. B. Low, “Ground target tracking using UAV with input constraints,” Journal of Intelligent & Robotic Systems, vol. 69, no. 1-4, pp. 417–429. 2013.\nR. Li, M. Chen, Q. X. Wu, and J. Y. Liu, “Robust adaptive tracking control for unmanned helicopter with constraints,” International Journal of Advanced Robotic Systems, vol. 14, no. 3, pp. 1–12, 2017.\nD. A. Lawrence, “Lyapunov vector fields for UAV flock coordination,” Proc. of the 2nd AIAA Unmanned Unlimited Conf., Workshop & Exhibit, San Diego, California, USA, pp.1–8, Sep. 2003.\nA. J. Munoz-Vazquez, V. Parra-Vega, and A. Sanchez, “A passive velocity field control for navigation of quadrotors with model-free integral sliding modes,” Journal of Intelligent & Robotic Systems, vol. 73 no. 1-4, pp. 373–385. 2014.\nH. Oh, S. Kim, H. Shin, and A. Tsourdos, “Coordinated standoff tracking using path shaping for multiple UAVs,” IEEE Transactions on Aerospace and Electronic Systems, vol. 50, no. 1, pp. 348–363, 2014.\nH. Oh, S. Kim, H. Shin, B. A. White, A. Tsourdos, and C. A. Rabbath, “Rendezvous and standoff target tracking guidance using differential geometry,” Journal of Intelligent & Robotic Systems, vol. 69, no. 1-4, pp. 389–405. 2013.\nZ. Q. Song, H. X. Li, C. L. Chen, X. Z. Zhou, and F. Xu, “Coordinated standoff tracking of moving targets using differential geometry,” Journal of Zhejiang University SCIENCE C vol. 15, no. 4, pp. 284–292, 2014.\nS. Yoon, S. Park, and Y. Kim, “Circular motion guidance law for coordinated standoff tracking of a moving target,” IEEE Transactions on Aerospace and Electronic Systems, vol. 49, no. 4, pp. 2440–2462, 2013.\nS. Kim, H. Oh, and A. Tsourdos, “Nonlinear model predictive coordinated standoff tracking of a moving ground vehicle,” Journal of Guidance, Control, and Dynamics, vol. 36, no. 2, pp. 557–566, 2013.\nH. Oh, S. Kim, and A. Tsourdos, “Road-map-assisted standoff tracking of moving ground vehicle using nonlinear model predictive control,” IEEE Transactions on Aerospace and Electronic Systems, vol. 51, no. 2, pp. 975–986, 2015.\nM. Quigley, M. A. Goodrich, S. Griffiths, A. Eldredge, and R. W. Beard, “Target acquisition, localization, and surveillance using a fixed-wing mini-UAV and gimbaled camera,” Proc. of the IEEE international Conference on Robotics and Automation, Barcelona, Spain, pp. 2600–2605, Apr. 2005.\nD. Kingston and R. Beard, “UAV splay state configuration for moving targets in wind,” Advances in Cooperative Control and Optimization, vol. 369, Springer-Verlag, Berlin, Germany, pp. 109–128, 2007.\nD. A. Lawrence, E. W. Frew, and W. J. Pisano, “Lyapunov vector fields for autonomous unmanned aircraft flight control,” Journal of Guidance, Control, and Dynamics, vol. 31, no. 5, pp. 1220–1229, 2008.\nE. W. Frew, D. A. Lawrence, and S. Morris, “Coordinated standoff tracking of moving targets using Lyapunov guidance vector fields,” Journal of Guidance, Control, and Dynamics, vol. 31, no. 2, pp. 290–306, 2008.\nS. Lim, Y. Kim, D. Lee, and H. Bang, “Standoff target tracking using a vector field for multiple unmanned aircrafts,” Journal of Intelligent & Robotic Systems, vol. 69, no. 1-4, pp. 347–360. 2013.\nH. Oh, S. Kim, A. Tsoutdos, and B. A. White, “Decentralised standoff tracking of moving targets using adaptive sliding mode control for UAVs,” Journal of Intelligent & Robotic Systems, vol. 76, no. 1, pp. 169–183, 2014.\nH. Chen, K. Chang, and C. S. Agate, “UAV path planning with tangent-plus-Lyapunov vector field guidance and obstacle avoidance,” IEEE Transactions on Aerospace and Electronic Systems, vol. 49, no. 2, pp. 840–856, 2013.\nH. Oh, S. Kim, H. Shin, and A. Tsoutdos, “Coordinated standoff tracking of moving target groups using multiple UAVs,” IEEE Transactions on Aerospace and Electronic Systems, vol. 51, no. 2, pp. 1501–1514, 2015.\nT. H. Summers, M. R. Akella, and M. J. Mears, “Coordinated standoff tracking of moving targets: Control laws and information architectures,” Journal of Guidance, Control, and Dynamics, vol. 32, no. 1, pp. 56–69, 2009.\nH. Shen, F. Li, S. Y. Xu, and V. Sreeram, “Slow state variables feedback stabilization for semi-Markov jump systems with singular perturbations,” IEEE Transactions on Automatic Control, vol. 63, no. 8, pp. 2709–2714, 2017.\nY. B. Chen, G. C. Luo, Y. S. Mei, J. Q. Yu, and X. L. Su, “UAV path planning using artificial potential field method updated by optimal control theory,” International Journal of Systems Science, vol. 47, no. 6, pp. 1407–1420, 2016.\nF. A. P. Lie and T. H. Go, “A collision-free formation reconfiguration control approach for unmanned aerial vehicles,” International Journal of Control, Automation and Systems, vol. 8, no. 5, pp. 1100–1107, 2010.\nA. Dang and J. Horn, “Formation control of leaderfollowing uavs to track a moving target in a dynamic environment,” Journal of Automation and Control Engineering, vol. 3, no. 1, pp. 1–8, 2015.\nR. Mahony, V. Kumar, and P. Corke, “Multirotor aerial vehicles: Modeling, estimation, and control of quadrotor,” IEEE Robotics & Autommation Magazine, vol. 19, no. 3, pp. 20–32, 2012.\nN. Sun, Y. C. Fang, and X. Zhang, “Energy coupling output feedback control of 4-DOF underactuated cranes with saturated inputs,” Automatica, vol. 49, no. 5, pp. 1318–1325, 2013.\nN. Sun and Y. C. Fang, “New energy analytical results for the regulation of underactuated overhead cranes: An end-effector motion-based approach,” IEEE Transactions on Industrial Electronics, vol. 59, no. 12, pp. 4723–4734, 2012.\nH. Shen, S. C. Huo, J. D. Cao, and T. W. Huang, “Generalized state estimation for Markovian coupled networks under round-robin protocol and redundant channels,” IEEE transactions on cybernetics, vol. 49, no. 4, pp. 1292–1301, 2019.\nW. H. Qi, G. D. Zong, and H. R. Karimi, “Observerbased adaptive SMC for nonlinear uncertain singular semi- Markov jump systems with applications to DC motor,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 9, pp. 2951–2960, 2018.\nY. Liang and H. Lee, “Decentralized formation control and obstacle avoidance for multiple robots with nonholonomic constraints,” Proc. of American Control Conference, Mineapolis, Minnesota, USA, pp. 5591–5601, Jun. 2006.\nL. A. G. Delgado and A. E. D. Lopez, “Formation control for quad-rotor aircrafts based on potential functions,” Proc. of Mexican Control and Automation Conference, Zacatecas, Mexico, 2009.\nA. R. Teel, “Global stabilization and restricted tracking for multiple integrators with bounded controls,” Systems & Control Letters, vol. 18, no. 3, pp. 165–171, 1992.\nA. Sanchez, P. Garcia, P. Castillo, and R. Lozano, “Simple real-time stabilization of vertical takeoff and landing aircraft with bounded signals,” Journal of Guidance, Control, and Dynamics, vol. 31, no. 4, pp. 1166–1176, 2008.\nK. Lee, J. Back, and I. Choy, “Nonlinear disturbance observer based robust attitude tracking controller for quadrotor UAVs.” International Journal of Control, Automation and Systems, vol. 12, no. 6, pp. 1266–1275, 2014.\nW. C. Zheng and M. Chen, “Tracking control of manipulator based on high-order disturbance observer,” IEEE Access, vol. 6, pp. 26753–26764. 2018.\nM. Chen, P. Shi, and C. C. Lim, “Robust constrained control for MIMO nonlinear systems based on disturbance observer,” IEEE Transaction on Automatic Control, vol. 60, no. 12, pp. 3281–3286, 2015.",{"VOID":1108},"10.1007\u002Fs12555-019-0101-x","2024-09-04T20:36:08.290+00:00","http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs12555-019-0101-x",[1112,1127,1140,1155],{"id":1113,"sortIndex":23,"researcher":22,"roles":1114,"affiliations":1115,"properties":1124,"displayName":1126,"givenName":22,"familyName":22},"a4b46176-c4a5-42d0-9467-512f7050a218",[149],[1116],{"id":1117,"sortIndex":23,"affiliation":1118,"properties":22},"5082365e-b3ae-4b5e-b261-395651070e59",{"id":1117,"createTime":22,"updateTime":22,"relativeEntities":1119,"slug":22,"properties":1120,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1123,"statistic":22},[],{"title":1121},{"VI":1122},"School of Electronics and Information, Jiangsu University of Science 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W. Brockett, R. S. Millman, and H. J. Sussmann, Differential Geometric Control Theory, Birkhauser, Basel, 1983.",{},{"id":22,"text":1352,"url":22,"identifiers":1353},"Z. D. Sun, S. S. Ge, W. Huo, and T. H. Lee, “Stabilization of nonholonomic chained systems via non-regular feedback linearization,” Systems and Control Letters, vol. 44, no. 4, pp. 279–289, 2001. [click]",{"doi":1354},"10.1016\u002FS0167-6911(01)00148-7",{"id":22,"text":1356,"url":22,"identifiers":1357},"X. Y. Zheng and Y. Q. Wu, “Adaptive output feedback stabilization for nonholonomic systems with strong nonlinear drifts,” Nonlinear Analysis: Theory, Methods and Applications, vol. 70, no. 2, pp. 904–920, 2009. [click]",{"doi":1358},"10.1016\u002Fj.na.2008.01.037",{"id":22,"text":1360,"url":22,"identifiers":1361},"F. Z. Gao, F. S. Yuan, and H. J. Yao, “Robust adaptive control for nonholonomic systems with nonlinear parameterization,” Nonlinear Analysis: Real World Applications, vol. 11, no. 4, pp. 3242–3250, 2010. [click]",{"doi":1362},"10.1016\u002Fj.nonrwa.2009.11.019",{"id":22,"text":1364,"url":22,"identifiers":1365},"F. Z. Gao, F. S. Yuan, H. J. Yao, and X. W. Mu, “Adaptive stabilization of high-order nonholonomic systems with strong nonlinear drifts,” Applied Mathematical Modelling, vol. 35, no. 9, pp. 4222–4233, 2011.",{"doi":1366},"10.1016\u002Fj.apm.2011.02.042",{"id":22,"text":1368,"url":22,"identifiers":1369},"M. Krstic and H. Deng, Stabilization of Nonlinear Uncertain Systems, Springer, New York, 1998.",{},{"id":22,"text":1371,"url":22,"identifiers":1372},"H. Deng, M. Krstic, and R. J. Williiams, “Stabilization of stochastic nonlinear systems driven by noise of unknown covariance,” IEEE Transactions on Automatic Control, vol. 46, no. 8, pp. 1237–1253, 2001. [click]",{"doi":1373},"10.1109\u002F9.940927",{"id":22,"text":1375,"url":22,"identifiers":1376},"S. C. Tong, Y. Li, Y. M. Li, and Y. J. liu, “Observer-based adaptive fuzzy backstepping control for a class of stochastic nonlinear strict-feedback systems,” IEEE Transactions on Systems, Man, and Cybernetics, Part B, vol. 41, pp. 1693–1704, 2011. [click]",{"doi":1377},"10.1109\u002FTSMCB.2011.2159264",{"id":22,"text":1379,"url":22,"identifiers":1380},"X. Yu and X. J. Xie, “Output feedback regulation of stochastic nonlinear systems with stochastic iISS inverse dynamics,” IEEE Transactions on Automatic Control, vol. 55, no. 2, pp. 304–320, 2010. [click]",{"doi":1381},"10.1109\u002FTAC.2009.2034924",{"id":22,"text":1383,"url":22,"identifiers":1384},"J. Fu, R. C. Ma, and T. Y. Chai, “Global finite-time stabilization of a class of switched nonlinear systems with the powers of positive odd rational numbers,” Automatica, vol. 54, pp. 360–373, 2015. [click]",{"doi":1385},"10.1016\u002Fj.automatica.2015.02.023",{"id":22,"text":1387,"url":22,"identifiers":1388},"N. Duan and X. J. Xie, “Further results on output-feedback stabilization for a class of stochastic nonlinear systems,” IEEE Transactions on Automatic Control, vol. 56, no. 5, pp. 1208–1213, 2011. [click]",{"doi":1389},"10.1109\u002FTAC.2011.2107112",{"id":22,"text":1391,"url":22,"identifiers":1392},"X. Yu, X. J. Xie, and Y. Q. Wu, “Decentralized adaptive output-feedback control for stochastic interconnected systems with stochastic unmodeled dynamic interactions,” International Journal of Adaptive Control and Signal Processing, vol. 25, no. 8, pp. 740–757, 2011. [click]",{"doi":1393},"10.1002\u002Facs.1240",{"id":22,"text":1395,"url":22,"identifiers":1396},"C. R. Zhao and X. J. Xie, “Output feedback stabilization using small-gain method and reduced-order observer for stochastic nonlinear systems,” IEEE Transactions on Automatic Control, vol. 58, no. 2, pp. 523–529, 2013. [click]",{"doi":1397},"10.1109\u002FTAC.2012.2208313",{"id":22,"text":1399,"url":22,"identifiers":1400},"X. J. Xie, C. R. Zhao, and N. Duan, “Further results on state feedback stabilization of stochastic high-order nonlinear system,” Science China Information Sciences, vol. 57, no. 7, 072202:1-072202:14, 2014.",{},{"id":22,"text":1402,"url":22,"identifiers":1403},"X. J. Xie and C. R. Zhao, “Global stabilization of stochastic high-order feedforward nonlinear systems with timevarying delay,” Automatica, vol. 50, no. 1, pp. 203–210, 2014. [click]",{"doi":1404},"10.1016\u002Fj.automatica.2013.09.044",{"id":22,"text":1406,"url":22,"identifiers":1407},"X. J. Xie, X. H. Zhang, K. M. Zhang, “Finite-time state feedback stabilization of stochastic high-order nonlinear feedforward systems,” International Journal of Control, vol. 89, no. 7, pp. 1332–1341, 2016. [click]",{"doi":1408},"10.1080\u002F00207179.2015.1129439",{"id":22,"text":1410,"url":22,"identifiers":1411},"X. J. Xie and L. Liu, “A homogeneous domination approach to state feedback of stochastic high-order nonlinear systems with time-varying delay,” IEEE Transactions on Automatic Control, vol. 58, no. 2, pp. 494–499, 2013. [click]",{"doi":1412},"10.1109\u002FTAC.2012.2208297",{"id":22,"text":1414,"url":22,"identifiers":1415},"X. Y. Qin, “State-feedback stablization for a class of highorder stochastic nonlinear systems,” Journal of Anhui University (Natural Science Edition), vol. 36, no. 4, pp. 7–12, 2012.",{},{"id":22,"text":1417,"url":22,"identifiers":1418},"J. Wang, H. Q. Gao, and H. Y. Li, “Adaptive robust control of nonholonomic systems with stochastic disturbance,” Science in China: Series F, vol. 49, no. 2, pp. 189–207, 2006. [click]",{"doi":1419},"10.1007\u002Fs11425-005-0022-4",{"id":22,"text":1421,"url":22,"identifiers":1422},"Y. L. Liu and Y. Q. Wu, “Output feedback control for nonholonomic systems with growth rete restriction,” Asian Journal of Control, vol. 13, no. 1, pp. 177–185, 2011. [click]",{"doi":1423},"10.1002\u002Fasjc.230",{"id":22,"text":1425,"url":22,"identifiers":1426},"Y. Zhao, J. B. Yu, and Y. Q. Wu, “State-feedback stabilization for a class of more general high order stochastic nonholonomic systems,” Int.J.Adapt.Control Singal Process, vol. 25, no. 8, pp. 687–706, 2011.",{"doi":1427},"10.1002\u002Facs.1233",{"id":22,"text":1429,"url":22,"identifiers":1430},"X. Y. Qin, “Adaptive exponential stabilization for a class of stochastic nonholonomic systems,” Abstract and Applied and Analysis, vol. 2013, no. 2, pp. 1–6, 2013.",{},{"id":22,"text":1432,"url":22,"identifiers":1433},"M. S. Mahmoud, Switched Time-delay Systems, Springer-Verlag, Boston, 2010.",{"doi":1434},"10.1007\u002F978-1-4419-6394-9",{"id":22,"text":1436,"url":22,"identifiers":1437},"C. S. Tong, M. Y. Li, G. Feng, and T. Li, “Observer-based adaptive fuzzy backstepping dynamic surface control for a class of nonlinear systems with unknown time delays,” IET Control Theory and Applications, vol. 5, no. 12, pp. 1426–1438, 2011. [click]",{"doi":1438},"10.1049\u002Fiet-cta.2010.0632",{"id":22,"text":1440,"url":22,"identifiers":1441},"Y. Y. Wu, H. Z. Diao, and Y. Q. Wu, “Robust stabilization of nonholonomic systems with unknown time delays,” Proceedings of the 30th Chinese control Conferences, Yantai, China, pp. 1166–1171, 2011.",{},{"id":22,"text":1443,"url":22,"identifiers":1444},"F. G. Gao, F. S. Yuan, and Y. Q. Wu, “State-feedback stabilization for stochastic nonholonomic systems with timevarying delays,” IET Control Theory and Applications, vol. 12, no. 17, pp. 2593–2600, 2012.",{"doi":1445},"10.1049\u002Fiet-cta.2011.0746",{"id":22,"text":1447,"url":22,"identifiers":1448},"S. J. Liu, S. S. Ge, and J. F. Zhang, “Adaptive outputfeedback control for a class of uncertain stochastic nonlinear system with time delays,” International Journal of Control, vol. 81, no. 8, pp. 1210–1220, 2008. [click]",{"doi":1449},"10.1080\u002F00207170701598478",{"id":22,"text":1451,"url":22,"identifiers":1452},"J. Fu, R. C. Ma, and T. Y. Chai, “tAdaptive finite-time stabilization of a class of uncertain nonlinear systems via logicbased switchings,” IEEE Transactions on Automatic Control, 10.1109\u002FTAC.2017.2705287",{"doi":1453},"10.1109\u002FTAC.2017.2705287",{"id":22,"text":1455,"url":22,"identifiers":1456},"L. G. Wu, H. J. Gao, and C. H. Wang, “Quasi sliding mode control of differential linear repetitive processes with unknown input disturbance,” IEEE Transactions on Industrial Electronics, vol. 58, no. 7, pp. 3059–3068, 2011. [click]",{"doi":1457},"10.1109\u002FTIE.2010.2072891",{"id":22,"text":1459,"url":22,"identifiers":1460},"J. X. Liu, W. S. Luo, X. Z. Yang, and L. G. Wu, “Robust model-based fault diagnosis for PEM fuel cell air-feed system,” IEEE Transactions on Industrial Electronics, vol. 63, no. 5, pp. 3261–3270, 2016. [click]",{"doi":1461},"10.1109\u002FTIE.2016.2535118",{"id":22,"text":1463,"url":22,"identifiers":1464},"L. G. Wu, W. X. Zheng, and H. J. Gao, “Dissipativity-based sliding mode control of switched stochastic systems,” IEEE Transactions on Automatic Control, vol. 58, no. 3, pp. 785–791, 2013. [click]",{"doi":1465},"10.1109\u002FTAC.2012.2211456",{"id":22,"text":1467,"url":22,"identifiers":1468},"W. Lin and C. J. Qian, “Adaptive control of nonlinearly parameterized systems: a non-smooth feedback framework,” IEEE Transactions on Automatic Control, vol. 47, no. 5, pp. 757–774, 2002. [click]",{"doi":1469},"10.1109\u002FTAC.2002.1000270",{"id":22,"text":1471,"url":22,"identifiers":1472},"H. K. Khalil, Nonlinear Systems, 2nd Edition, Prentice-Hall, Upper Saddle River, NJ, 1996.",{},{"id":1474,"createTime":1475,"updateTime":1476,"relativeEntities":1477,"slug":1478,"properties":1479,"entityType":138,"verifyStatus":139,"verifyTime":1490,"verifyNote":141,"languages":22,"translateLanguages":22,"viewCount":23,"primaryUrl":1491,"fullTextUrl":22,"authors":1492,"publicationType":230,"publisherRelationship":1536,"citationCount":23,"citationInfo":1588,"publishDate":1591,"publishYear":1589,"citationAnalyzeStatus":1344,"lastCitationAnalyze":1592,"indexDatabases":1593,"openAccess":22,"references":22,"isForceReanalyzing":286},"b738f9a6-2f9e-4e4a-80e3-95721ef12ee4","2023-11-25T18:13:02.997+00:00","2026-07-27T17:44:42.894+00:00",[],"A-New-Geometric-Subproblem-to-Extend-Solvability-of-Inverse-Kinematics-Based-on-Screw-Theory-for-6R-Robot-Manipulators",{"abstract":1480,"title":1482,"gsPaper":1484,"references":1486,"doi":1488},{"EN":1481},"Geometric inverse kinematics procedures that divide the whole problem into several subproblems with known solutions, and make use of screw motion operators have been developed in the past for 6R robot manipulators. These geometric procedures are widely used because the solutions of the subproblems are geometrically meaningful and numerically stable. Nonetheless, the existing subproblems limit the types of 6R robot structural configurations for which the inverse kinematics can be solved. This work presents the solution of a novel geometric subproblem that solves the joint angles of a general anthropomorphic arm. Using this new subproblem, an inverse kinematics procedure is derived which is applicable to a wider range of 6R robot manipulators. The inverse kinematics of a closed curve were carried out, in both simulations and experiments, to validate computational cost and realizability of the proposed approach. Multiple 6R robot manipulators with different structural configurations were used to validate the generality of the method. The results are compared with those of other methods in the screw theory framework. The obtained results show that our approach is the most general and the most efficient.",{"EN":1483},"A New Geometric Subproblem to Extend Solvability of Inverse Kinematics Based on Screw Theory for 6R Robot Manipulators",{"VOID":1485},"[\"5079153396374350029\"]",{"VOID":1487},"O. Khatib and B. Siciliano, Springer Handbook of Robotics, Springer, 2008.\nM. L. Husty, M. Pfurner, and H.-P. Schröcker, “A new and efficient algorithm for the inverse kinematics of a general serial 6r manipulator,” Mechanism and Machine theory, vol. 42, no. 1, pp. 66–81, 2007.\nA. T. Hasan, A. M. S. Hamouda, N. Ismail, and H. Al-Assadi, “An adaptive-learning algorithm to solve the inverse kinematics problem of a 6 DoF serial robot manipulator,” Advances in Engineering Software, vol. 37, no. 7, pp. 432–438, 2006.\nA. Casalino, A. M. Zanchettin, and P. Rocco, “Online planning of optimal trajectories on assigned paths with dynamic constraints for robot manipulators,” Proc. of IEEE\u002FRSJ International Conference on Intelligent Robots and Systems, pp. 979–985, 2016.\nS. S. Pchelkin, A. S. Shiriaev, A. Robertsson, and L. B. Freidovich, “Integrated time-optimal trajectory planning and control design for industrial robot manipulator,” Proc. of IEEE\u002FRSJ International Conference on Intelligent Robots and Systems, pp. 2521–2526, 2013.\nH. Wei, T. Gu, B. Yang, and Z. Shao, “Compliance control on 6-DoF robot modular manipulator with fuzzy methodology,” Proc. of 12th World Congress on Intelligent Control and Automation, pp. 3242–3247, 2016.\nI. Bonilla, M. Mendoza, E. J. Gonzalez-Galvan, C. Chavez-Olivares, A. Loredo-Flores, and F. Reyes, “Path-tracking maneuvers with industrial robot manipulators using uncalibrated vision and impedance control,” IEEE Trans. on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 42, no. 6, pp. 1716–1729, 2012.\nC. Crane, J. Rico, and J. Duffy, “Screw theory and its application to spatial robot manipulators,” Center for Intelligent Machines and Robotics, University of Florida, Gainesville, FL, Tech. Rep., 2009.\nR. M. Murray, Z. Li, S. S. Sastry, and S. S. Sastry, A Mathematical Introduction to Robotic Manipulation, CRC press, 1994.\nB. Paden, Kinematics and Control Robot Manipulators, PhD thesis, Department of Electrical Engineering and Computer Sciences, University of California, 1986.\nE. Sariyildiz and H. Temeltas, “Solution of inverse kinematic problem for serial robot using dual quaterninons and plücker coordinates,” Proc. of IEEE\u002FASME International Conference on Advanced Intelligent Mechatronics, pp. 338–343, 2009.\nQ. Chen, S. Zhu, and X. Zhang, “Improved inverse kinematics algorithm using screw theory for a six-dof robot manipulator,” International Journal of Advanced Robotic Systems, vol. 12, no. 10, p. 140, 2015.\nI.-M. Chen and Y. Gao, “Closed-form inverse kinematics solver for reconfigurable robots,” Proc. of IEEE International Conference on Robotics and Automation, vol. 3, pp. 2395–2400, 2001.\nT. Yue-sheng and X. Ai-Ping, “Extension of the second paden-kahan sub-problem and its’ application in the inverse kinematics of a manipulator,” Proc. of IEEE Conference on Robotics, Automation and Mechatronics, pp. 379–381, 2008.\nJ. Leoro, C. Betancourt, L. Hsien, H. Te-Sheng, and C.-S. Wang, “An improved inverse kinematics solution of 6r-dof robot manipulators with euclidean wrist using dual quaternions,” Proc. of CACS International Conference on Automatic Control, pp. 77–82, 2016.\nE. Sariyildiz, E. Cakiray, and H. Temeltas, “A comparative study of three inverse kinematic methods of serial industrial robot manipulators in the screw theory framework,” International Journal of Advanced Robotic Systems, vol. 8, no. 5, p. 64, 2011.\nJ. Funda, R. H. Taylor, and R. P. Paul, “On homogeneous transforms, quaternions, and computational efficiency,” IEEE Trans. on Robotics and Automation, vol. 6, no. 3, pp. 382–388, 1990.\nR. Mukundan, “Quaternions: From classical mechanics to computer graphics, and beyond,” Proc. of the 7th Asian Technology Conference in Mathematics, pp. 97–105, 2002.\nH. Bruyninckx and J. Shutter, “Introduction to intelligent robotics,” Katholieke Universiteit de Leuven, Tech. 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L\n                        2–L\n                        ∞ filtering problem for continuous-time polytopic uncertain stochastic time-delay systems is investigated. The main purpose is to design a full-order filter guaranteeing a prescribed L\n                        2–L\n                        ∞ attenuation level for the filtering error system. A simple alternative proof is given for an enhanced LMI (linear matrix inequality) representation of L\n                        2–L\n                        ∞ performance. Based on the criterion which keeps Lyapunov matrices out of the products of system dynamic matrices, a sufficient condition for the existence of a robust estimator is formulated in terms of LMIs. The corresponding filter design is cast into a convex optimization problem. A numerical example is employed to demonstrate the feasibility and advantage of the proposed design.",{"EN":1604},"Improved L 2–L ∞ filtering for stochastic time-delay 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V. Javad and G. Karolos M, “Delay-dependent H ∞ filtering for time-delayed LPV systems,” Systems and Control Letters, vol. 57, no. 4, pp. 290–299, 2008.",{"doi":779},{"id":22,"text":1724,"url":22,"identifiers":1725},"X. M. Zhang and Q. L. Han, “Robust H ∞ filtering for a class of uncertain linear systems with time-varying delay,” Automatica, vol. 44, no. 1, pp. 157–166, 2008.",{},{"id":1727,"text":1728,"url":1729,"identifiers":1730},"aec52c32-1caa-4170-b5b7-332171c38d97","H. C. Choi, D. Chwa, and S. K. Hong. “An LMI approach to robust reduced-order H ∞ filter design for polytopic uncertain systems,” International Journal of Control, Automation, and Systems, vol. 7, no. 3, pp. 487–494, 2009.","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs12555-009-0319-0",{"doi":1731},"10.1007\u002Fs12555-009-0319-0",{"id":775,"text":1733,"url":777,"identifiers":1734},"A. W. Pila, U. Shaked, and C. E. de Souza, “H ∞ filtering for continuous-time linear systems with delay,” IEEE Transactions on Automatic Control, vol. 44, no. 7, pp. 1412–1417, 1999.",{"doi":779},{"id":1736,"text":1737,"url":1738,"identifiers":1739},"7dd2e32f-85a1-488d-ac9b-392a5bec3b2e","R. M. Palhares and P. L. D. Peres, “Robust filtering with guaranteed energy-to-peak performance an LMI approach,” Automatica, vol. 36, pp. 851–858, 2000.","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS1474667017563089",{"doi":1740},"10.1016\u002Fs1474-6670(17)56308-9",{"id":1742,"text":1743,"url":1744,"identifiers":1745},"39b20522-fb58-4c3e-a2fa-8d119313fec1","H. J. Gao, J. Lam, and C. H. Wang, “Robust energy-to-peak filter design for stochastic time-delay systems,” System and Control Letters, vol. 55, pp. 101–111, 2006.","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0167691105000939",{"doi":1746},"10.1016\u002Fj.sysconle.2005.05.005",{"id":775,"text":1748,"url":777,"identifiers":1749},"H. J. Gao and C. H. Wang, “Robust L 2 - L ∞ filtering for uncertain systems with multiple time- varying state delays,” IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 50, no. 4, pp. 594–599, 2003.",{"doi":779},{"id":1751,"text":1752,"url":1753,"identifiers":1754},"a66f0028-cc15-466b-b9e1-b9531a6e128b","J. T. Watson and K. M. Grigoriadis, “Optimal unbiased filtering via linear matrix inequalities,” System and Control Letters, vol. 42, pp. 363–377, 1998.","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0167691198000425",{"doi":1755},"10.1016\u002Fs0167-6911(98)00042-5",{"id":775,"text":1757,"url":777,"identifiers":1758},"D. A. Wilson, “Convolution and Hankel operator norms for linear systems,” IEEE Transactions on Automatic Control, vol. 34, no. 1, pp. 94–97, 1989.",{"doi":779},{"id":1760,"text":1761,"url":1762,"identifiers":1763},"de25dd0b-6a77-4c76-8101-4a5653c4075d","A. G. Wu and G. R. Duan, “On delay-independent stability criteria for linear time-delay systems,” International Journal of Automation and Computing, vol. 4, no. 1, pp. 95–100, 2007.","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11633-007-0095-3",{"doi":1764},"10.1007\u002Fs11633-007-0095-3",{"id":775,"text":1766,"url":777,"identifiers":1767},"Y. He, M. Wu, J. H. She, and G. P. Liu, “Parameter-dependent Lyapunov functional for stability of time-delay systems with polytopic-type uncertainties,” IEEE Transactions on Automatic Control, vol. 49, no. 5, pp. 828–832, 2004.",{"doi":779},{"id":775,"text":1769,"url":777,"identifiers":1770},"Q. L. Han, “On robust stability of neutral systems with time-varying discrete delay and norm-bounded uncertainty,” Automatica, vol. 40, no. 6, pp. 1087–1092, 2004.",{"doi":779},{"id":22,"text":1772,"url":22,"identifiers":1773},"D. Hinrichsen and A. J. Pritchard, “Stochastic H ∞,” SIAM J. Control Optim, vol. 36, no. 5, pp. 1504–1538, 1998.",{},{"id":775,"text":1775,"url":777,"identifiers":1776},"S. Xu and T. Chen, “Reduced-order H ∞ filtering for stochastic systems,” IEEE Transactions on Signal Process, vol. 50, no. 12, pp. 2998–3007, 2002.",{"doi":779},{"id":775,"text":1778,"url":777,"identifiers":1779},"E. Gershon, D. J. N. Limebeer, U. Shaked, and I. Yaesh, “Robust H ∞ filtering of stationary continuous-time linear systems with stochastic uncertainties,” IEEE Transactions on Automatic Control, vol. 46, no. 11, pp. 1788–1793, 2001.",{"doi":779},{"id":22,"text":1781,"url":22,"identifiers":1782},"A. G. Wu and G. R. Duan, “Robust H ∞ estimation for uncertain continuous-time systems,” Proc. of the 4th International Conference on Machine Learning and Cytbernetic, Guangzhou, China, pp. 448–453, 2004.",{}]