Model predictive control and its application in agriculture: A review

Computers and Electronics in Agriculture - Tập 151 - Trang 104-117 - 2018
Ying Ding, Liang Wang, Yongwei Li, Daoliang Li

Tài liệu tham khảo

Adetola, 2009, Adaptive model predictive control for constrained nonlinear systems, Syst. Control Lett., 58, 320, 10.1016/j.sysconle.2008.12.002 Adetola, 2011, Robust adaptive MPC for constrained uncertain nonlinear systems, Int. J. Adapt Control Signal Process., 25, 155, 10.1002/acs.1193 Afram, 2014, Theory and applications of HVAC control systems - a review of model predictive control (MPC), Build. Environ., 72, 343, 10.1016/j.buildenv.2013.11.016 Aguilar, 2016, Predictive control of irrigation canals – robust design and real-time implementation, Water Resour. Manage., 30, 3829, 10.1007/s11269-016-1387-6 Akçakaya, 2009, An application of robust model predictive control with integral action, Instrum Sci. Technol., 37, 410, 10.1080/10739140903087725 Akpan, 2011, Nonlinear model identification and adaptive model predictive control using neural networks, Isa Transactions, 50, 177, 10.1016/j.isatra.2010.12.007 Alessio, 2009, A survey on explicit model predictive control, Nonlinear Model Predictive Control, 345, 10.1007/978-3-642-01094-1_29 Alrifaee, B. et al., 2016. Coordinated Non-Cooperative Distributed Model Predictive Control for Decoupled Systems Using Graphs. In: Ifac Workshop on Distributed Estimation & Control in Networked Systems Necsys. vol. 49(22), pp. 216–221. Álvarez, 2013, Constrained predictive control of an irrigation canal, J. Irrig. Drain. Eng., 139, 841, 10.1061/(ASCE)IR.1943-4774.0000619 Backman, 2012, Navigation system for agricultural machines: nonlinear model predictive path tracking, Comput. Electron. Agric., 82, 32, 10.1016/j.compag.2011.12.009 Barata, 2014, Distributed MPC for green thermally comfortable buildings based on an electro-thermal modular approach, Procedia Technol., 17, 772, 10.1016/j.protcy.2014.10.211 Bayer, F.A. et al., 2016. A tube-based approach to nonlinear explicit MPC. In: 55th IEEE Conference on Decision and Control (CDC) Las Vegas, NV, pp. 4059–4064. Bemporad, 1999, Control of systems integrating logic, dynamics, and constraints, Automatica, 35, 407, 10.1016/S0005-1098(98)00178-2 Bounkhel, 2015, Optimal harvesting effort for nonlinear predictive control model for a single species fishery, Math. Problems Eng., 2015, 1, 10.1155/2015/367593 Breckpot, 2013, Flood control with model predictive control for river systems with water reservoirs, J. Irrig. Drain. Eng., 139, 532, 10.1061/(ASCE)IR.1943-4774.0000577 Bumroongsri, 2014, Off-line robust constrained mpc for linear time-varying systems with persistent disturbances, Math. Problems Eng., 2014, 282 Camacho, 2015, Robust adaptive model predictive control of a solar plant with bounded uncertainties, Int. J. Adapt Control Signal Process., 11, 311, 10.1002/(SICI)1099-1115(199706)11:4<311::AID-ACS410>3.0.CO;2-K Cannon, 2012, Stochastic tube MPC with state estimation, Automatica, 48, 536, 10.1016/j.automatica.2011.08.058 Cannon, 2011, Stochastic tubes in model predictive control with probabilistic constraints, IEEE Trans. Autom. Control, 56, 194, 10.1109/TAC.2010.2086553 Cariou, C. et al., 2010. Autonomous Maneuvers of a Farm Vehicle with a Trailed Implement in Headland. In: 7th International Conference on Informatics in Control, Automation and Robotics Funchal, Portugal, vol. 2. pp. 109–114. Christofides, 2013, Distributed model predictive control: a tutorial review and future research directions, Comput. Chem. Eng., 51, 21, 10.1016/j.compchemeng.2012.05.011 Clarke, 1987, Generalized predictive control—Part I. The basic algorithm, Automatica, 23, 137, 10.1016/0005-1098(87)90087-2 Clarke, D.W. et al., 1987. Generalized predictive control—Part II. Extensions and interpretations. Pergamon Press, Inc. 23 (2), 149–160. Coelho, 2005, Greenhouse air temperature predictive control using the particle swarm optimisation algorithm, Comput. Electron. Agric., 49, 330, 10.1016/j.compag.2005.08.003 Coen, 2008, Cruise control using model predictive control with constraints, Comput. Electron. Agric., 63, 227, 10.1016/j.compag.2008.03.003 Cutler, C.R., Ramakar, B.L., 1980. Dynamic matrix control — a computer control algorithm. In: Joint Automatic Control Conference. Dai, 2016, Distributed stochastic MPC of linear systems with additive uncertainty and coupled probabilistic constraints, IEEE Trans. Autom. Control, 62, 3474, 10.1109/TAC.2016.2612822 Delgoda, 2016, Irrigation control based on model predictive control (MPC): formulation of theory and validation using weather forecast data and AQUACROP model, Environ. Modell. Software, 78, 40, 10.1016/j.envsoft.2015.12.012 El Ghoumari, 2005, Non-linear constrained MPC: real-time implementation of greenhouse air temperature control, Comput. Electron. Agric., 49, 345, 10.1016/j.compag.2005.08.005 Farhadi, 2016, Distributed model predictive control with hierarchical architecture for communication: application in automated irrigation channels, Int. J. Control, 70, 059904 Fele, 2014, Coalitional model predictive control of an irrigation canal, J. Process Control, 24, 314, 10.1016/j.jprocont.2014.02.005 Fele, F. et al., 2013. Coalitional control: an irrigation canal case study. In: 10th IEEE International Conference on Networking, pp. 759–764. Figueiredo, 2013, SCADA system with predictive controller applied to irrigation canals, Control Eng. Pract., 21, 870, 10.1016/j.conengprac.2013.01.008 Froisy, 1994, Model predictive control: Past, present and future, Isa Trans., 33, 235, 10.1016/0019-0578(94)90095-7 Fukushima, 2007, Adaptive model predictive control for a class of constrained linear systems based on the comparison model, Automatica, 43, 301, 10.1016/j.automatica.2006.08.026 Gaida, D. et al., 2012. Nonlinear model predictive substrate feed control of biogas plants. In: 2012 20th Mediterranean Conference on Control & Automation (MED 2012). Barcelona, Spain, pp. 652–657. Gao, 2014, DMC-PD cascade control method of the automatic steering system in the navigation control of agricultural machines, Intell. Control Automation, Shenyang, China, 27, 2160 Garcia, 1982, Internal model control. A unifying review and some new results, Ind. Eng. Chem. Process Des. Dev, 21, 308, 10.1021/i200017a016 Garcia, 1986, Quadratic programming solution of dynamic matrix control (QDMC), Chem. Eng. Commun., 46, 73, 10.1080/00986448608911397 Garriga, 2010, Model predictive control tuning methods: a review, Ind. Eng. Chem. Res., 49, 3505, 10.1021/ie900323c Ghasemi, 2017, Robust tube-based MPC of constrained piecewise affine systems with bounded additive disturbances, Nonlinear Anal. Hybrid Syst, 26, 86, 10.1016/j.nahs.2017.04.007 Goebel, 2017, Semi-explicit MPC based on subspace clustering, Automatic, 83, 309, 10.1016/j.automatica.2017.06.036 González, 2014, Robust constrained economic receding horizon control applied to the two time-scale dynamics problem of a greenhouse, Opt. Control Appl. Methods, 35, 435, 10.1002/oca.2080 Grosdidier, G., et al., 1988. The IDCOM-M controller. In: Proceedings of the 1988 IFAC workshop on model based process control, pp. 31–36. Gruber, 2011, Nonlinear MPC based on a Volterra series model for greenhouse temperature control using natural ventilation, Control Eng. Pract., 19, 354, 10.1016/j.conengprac.2010.12.004 Guo, 2010, Fractional-order PID dynamic matrix control algorithm based on time domain, Intell. Control Automation, 208 Han, 2012, Model predictive control of the grain drying process, Math. Problems Eng., 2012, 857 Han, 2014, Nonlinear model-predictive control for industrial processes: an application to wastewater treatment process, IEEE Trans. Ind. Electron., 61, 1970, 10.1109/TIE.2013.2266086 Harinath, E. et al., 2016. Nonlinear model predictive control using polynomial optimization methods. In: American Control Conference (ACC). Boston, MA 1–6. Hashemy, 2013, Application of an in-line storage strategy to improve the operational performance of main irrigation canals using model predictive control, J. Irrig. Drain. Eng., 139, 635, 10.1061/(ASCE)IR.1943-4774.0000603 Hernandez, A. et al., 2014. Modeling and Nonlinear Model Predictive Control of a rotary disc dryer for fishmeal production. In: 13th European Control Conference (ECC) Univ Strasbourg, Strasbourg, FRANCE. 1819–1824. Hernandez, 2015, Towards the development of a smart flying sensor: illustration in the field of precision agriculture, Sensors (Basel), 15, 16688, 10.3390/s150716688 Horváth, 2014, Is it better to use gate opening as control variable than discharge to control irrigation canals?, J. Irrig. Drain. Eng., 141, 10.1061/(ASCE)IR.1943-4774.0000798 Horváth, 2015, New offset-free method for model predictive control of open channels, Control Eng. Pract., 41, 13, 10.1016/j.conengprac.2015.04.002 Horvath, K. et al., 2014. MPC control of water level in a navigation canal: The Cuinchy-Fontinettes case study. In: 13th European Control Conference (ECC) Univ Strasbourg, FRANCE. vol. 25 (6), pp. 1337–1342. Houska, 2011, An auto-generated real-time iteration algorithm for nonlinear MPC in the microsecond range, Automatica, 47, 2279, 10.1016/j.automatica.2011.08.020 Hu, 2011, Multi-objective control optimization for greenhouse environment using evolutionary algorithms, Sensors, 11, 5792, 10.3390/s110605792 Ito, K., 2012. Greenhouse temperature control with wooden pellet heater via model predictive control approach. In: 2012 20th Mediterranean Conference on Control & Automation (MED 2012). Barcelona, Spain, pp. 1542–1547. Kalman, 1960, A new approach to linear filtering and prediction problems, J. Basic Eng. Trans., 82, 35, 10.1115/1.3662552 Kalmari, 2014, Nonlinear model predictive control of hydraulic forestry crane with automatic sway damping, Comput. Electron. Agric., 109, 36, 10.1016/j.compag.2014.09.006 Kalmari, 2017, Coordinated motion of a hydraulic forestry crane and a vehicle using nonlinear model predictive control, Comput. Electron. Agric., 133, 119, 10.1016/j.compag.2016.12.013 Kamilaris, 2018, Deep learning in agriculture: a survey, Comput. Electron. Agric., 147, 70, 10.1016/j.compag.2018.02.016 Kayacan, 2015, Robust tube-based decentralized nonlinear model predictive control of an autonomous tractor-trailer system, IEEE/ASME Trans. Mechatron., 20, 447, 10.1109/TMECH.2014.2334612 Kayacan, 2014, Distributed nonlinear model predictive control of an autonomous tractor–trailer system, Mechatronics, 24, 926, 10.1016/j.mechatronics.2014.03.007 Kayacan, 2015, Learning in centralized nonlinear model predictive control: application to an autonomous tractor-trailer system, Control Syst. Technol. IEEE Trans. on, 23, 197, 10.1109/TCST.2014.2321514 Kayacan, 2015, Towards agrobots: Identification of the yaw dynamics and trajectory tracking of an autonomous tractor, Comput. Electron. Agric., 115, 78, 10.1016/j.compag.2015.05.012 Kayacan, 2015, Robust trajectory tracking error model-based predictive control for unmanned ground vehicles, IEEE/ASME Trans. Mechatron., 21, 806, 10.1109/TMECH.2015.2492984 Kearney, M., Cantoni, M., 2012. MPC-based reference management for automated irrigation channels. In: 2nd Australian Control Conference (AUCC), Sydney, AUSTRALIA, pp. 349–354. Kearney, M. et al., 2011. Model predictive control for systems with scheduled load and its application to automated irrigation channels. In: 2011 International Conference on Networking, Sensing and Control (ICNSC 2011). Delft, Netherlands, pp. 186–191. Kearney, M. et al., 2011. Non-iterative distributed MPC for large-scale irrigation channels. In: 2011 Australian Control Conference (AUCC 2011). Melbourne, VIC, Australia, pp. 217–223. Kersbergen, 2016, Distributed model predictive control for railway traffic management, Transp. Res. Part C Emerging Technol., 68, 462, 10.1016/j.trc.2016.05.006 Kiselev, A. et al., 2016. Position control of a permanent magnet synchronous motor using generalized predictive control algorithm. In: International Symposium on Power Electronics, Electrical Drives, Automation and Motion, pp. 110–115. Kouvaritakis, 2010, Brief paper: explicit use of probabilistic distributions in linear predictive control, Automatica, 46, 1719, 10.1016/j.automatica.2010.06.034 Kraus, 2013, Moving horizon estimation and nonlinear model predictive control for autonomous agricultural vehicles, Comput. Electron. Agric., 98, 25, 10.1016/j.compag.2013.06.009 Lal, R., 1990. Soil Erosion and Land Degradation: The Global Risks. vol. 11. Springer, New York, pp. 129–172. Lee, 2011, Model predictive control: review of the three decades of development, Int. J. Control Autom. Syst., 9, 415, 10.1007/s12555-011-0300-6 Lee, 2014, From robust model predictive control to stochastic optimal control and approximate dynamic programming: a perspective gained from a personal journey, Comput. Chem. Eng., 70, 114, 10.1016/j.compchemeng.2013.10.014 Lemos, 2009, Adaptive and non-adaptive model predictive control of an irrigation channel, Networks Heterogeneous Media, 4, 303, 10.3934/nhm.2009.4.303 Li, A.M. et al., 2015. The research and design of Intelligent Wind Velocity- Temperature-CO 2 Control Model of Coop. In: IEEE International Conference on Information and Automation 2015. Lijiang, PEOPLES R CHINA, pp. 2715–2719. Li, 2012, FPGA based QDMC control for reverse-osmosis water desalination system, Desalination, 285, 83, 10.1016/j.desal.2011.09.037 Li, Y., 2014. On supervisory control of the Main Southern Channel. In: IEEE Conference on Control Applications (CCA) Nice, FRANCE, pp. 2165–2170. Limon, 2010, Robust tube-based MPC for tracking of constrained linear systems with additive disturbances, J. Process Control, 20, 248, 10.1016/j.jprocont.2009.11.007 Liu, 2012, Analysis of aquatic products price model using predictive control theory, J. Food Agric. Environ., 10, 1179 Liu, 2006, Process control based on principal component analysis for maize drying, Food Control, 17, 894, 10.1016/j.foodcont.2005.06.008 Lloyd, 2017, High resolution global gridded data for use in population studies, Sci. Data, 4, 10.1038/sdata.2017.1 Lu, 2009, Generalized predictive control using recurrent fuzzy neural networks for industrial processes, J. Chin. Inst. Eng., 32, 277, 10.1080/02533839.2009.9671504 Ma, G. et al., 2015. Modeling and predictive control of greenhouse temperature-humidity system based on MLD and time-series. In: 34th Chinese Control Conference (CCC) Hangzhou, CHINA, pp. 2234–2239. Maestre, J.M. et al., 2014. Human in the loop model Predictive Control: an irrigation canal case study. In: IEEE 53rd Annual Conference on Decision and Control (CDC) Los Angeles, CA, pp. 4:4881–4886. Marquis, P., Broustail, J.P., 1988. SMOC, A bridge between state space and model predictive controllers—application to the automation of a hydrotreating unit. In: Proc. of IFAC workshop on model based process control, pp. 37–43. McCarthy, 2014, Simulation of irrigation control strategies for cotton using Model Predictive Control within the VARIwise simulation framework, Comput. Electron. Agric., 101, 135, 10.1016/j.compag.2013.12.004 Mendes, 2017, A practical approach for hybrid distributed MPC, J. Process Control, 55, 30, 10.1016/j.jprocont.2017.01.001 Mogal, P.W., Warke, N., 2013. Model Predictive Control using LabVIEW. In: International Conference on Advances in Technology and Engineering, pp. 1–6. Moon, 2011, An adaptive dynamic matrix control with fuzzy-interpolated step-response model for a drum-type boiler-turbine system, IEEE Trans. Energy Convers., 26, 393, 10.1109/TEC.2011.2116023 Morari, 1999, Model predictive control: past, present and future, Comput. Chem. Eng., 23, 667, 10.1016/S0098-1354(98)00301-9 Negenborn, 2009, Distributed model predictive control of irrigation canals, Networks Heterogeneous Media, 4, 358, 10.3934/nhm.2009.4.359 Negenborn, R.R. et al., 2009. A non-iterative cascaded predictive control approach for control of irrigation canals. In: IEEE International Conference on Systems, Man and Cybernetics San Antonio, TX, pp. 3552–3557. Neshastehriz, A.R. et al., 2014. Water-level reference planning for automated irrigation channels via robust MPC. In: 13th European Control Conference (ECC) Univ Strasbourg, Strasbourg, France, pp. 1331–1336. Pan, Y., Wang, J., 2008. Robust model predictive control using a discrete-time recurrent neural network. In: International Symposium on Neural Networks: Advances in Neural Networks. Beijing, PEOPLES R CHINA 5263, pp. 883–892. Pannocchia, 2015, Distributed model predictive control, Opti. Control Appl. Methods, 36, 44 Pawlowski, 2012, Improving feedforward disturbance compensation capabilities in Generalized Predictive Control, J. Process Control, 22, 527, 10.1016/j.jprocont.2012.01.010 Pawlowski, 2012, A practical approach for Generalized Predictive Control within an event-based framework, Comput. Chem. Eng., 41, 52, 10.1016/j.compchemeng.2012.03.003 Pinon, 2005, Constrained predictive control of a greenhouse, Comput. Electron. Agric., 49, 317, 10.1016/j.compag.2005.08.007 Plessen, 2017, Reference trajectory planning under constraints and path tracking using linear time-varying model predictive control for agricultural machines, Biosyst. Eng., 153, 28, 10.1016/j.biosystemseng.2016.10.019 Pomeranz, K., 2009. The Great Himalayan Watershed: Water Shortages, Mega-Projects and Environmental Politics in China, India, and Southeast Asia. Asia-Pacific Journal: Japan Focus. Puig, V. et al., 2012. Model predictive control of combined irrigation and water supply systems: Application to the Guadiana river. In: 2012 9th IEEE International Conference on Networking, Sensing and Control (ICNSC). Beijing, China, pp. 85–90. Qin, 1997, An overview of industrial model predictive control technology, Control Eng. Pract., 93, 232 Qin, 2003, A survey of industrial model predictive control technology, Control Eng. Pract., 11, 733, 10.1016/S0967-0661(02)00186-7 Ramdani, M. et al., 2015. Multiscale fuzzy model-based short term predictive control of greenhouse microclimate. In: IEEE International Conference on Industrial Informatics, pp. 1348–1353. Rawlings, J.B., Mayne, D.Q., 2009. Model Predictive Control: Theory and Design. Richalet, 1978, Model predictive heuristic control: Applications to an industrial process, Automatica., 413, 10.1016/0005-1098(78)90001-8 Richalet, J. et al., 1976. Algorithmic control of industrial processes. Richalet, 1978, Model predictive heuristic control : applications to industrial processes, Automatica, 14, 413, 10.1016/0005-1098(78)90001-8 Roca, 2016, Predictive control applied to a solar desalination plant connected to a greenhouse with daily variation of irrigation water demand, Energies, 9, 194, 10.3390/en9030194 Sadjadi, E., Mohammad, 2013. Adaptive model predictive control. American Control Conference. Sadowska, A. et al., 2014. Hierarchical control of irrigation canals in the presence of disturbances: Framework and comparison. In: 13th European Control Conference (ECC) Univ Strasbourg, Strasbourg, France, pp. 1349–1354. Sadowska, 2014, Hierarchical Operation of Water Level Controllers: Formal Analysis and Application on a Large Scale Irrigation Canal, Water Resour. Manage., 28, 4999, 10.1007/s11269-014-0785-x Sadowska, A., et al., 2015. Human-in-the-loop control of an irrigation canal using time instant optimization Model Predictive Control. In: European Control Conference (ECC) Linz, Austria, pp. 3274–3279. Sadowska, 2015, Delivery-Oriented Hierarchical Predictive Control of an Irrigation Canal: Event-Driven Versus Time-Driven Approaches, IEEE Trans. Control Syst. Technol., 23, 1701, 10.1109/TCST.2014.2381600 Salahou, 2013, Research Journal of Applied Sciences Engineering and Technology-Review Article Control of an Irrigation Canal, Res. J. Appl. Sci. Eng. Technol., 5, 3916, 10.19026/rjaset.5.4453 Sanchez, 2002, Ecology. Soil fertility and hunger in Africa, Science, 295, 2019, 10.1126/science.1065256 Scattolini, 2009, Architectures for distributed and hierarchical Model Predictive Control – A review, J. Process Control, 19, 723, 10.1016/j.jprocont.2009.02.003 Scattolini, R., Colaneri, P., 2007. Hierarchical model predictive control. In: Decision and Control, 2007 IEEE Conference on, vol. 11(10). pp. 4803–4808. Seki, 2001, Industrial application of a nonlinear model predictive control to polymerization reactors, Control Eng. Pract., 9, 819, 10.1016/S0967-0661(01)00046-6 Shahdany, 2016, Improving Operation of a Main Irrigation Canal Suffering from Inflow Fluctuation within a Centralized Model Predictive Control System: Case Study of Roodasht Canal, Iran, J. Irrig. Drain. Eng., 142, 05016007:1, 10.1061/(ASCE)IR.1943-4774.0001087 Shen, 2013, Model-based control of natural ventilation in dairy buildings, Comput. Electron. Agric., 94, 47, 10.1016/j.compag.2013.02.007 Singh, 2015, Integrated Moving Horizon-Based Dynamic Real-Time Optimization and Hybrid MPC-PID Control of a Direct Compaction Continuous Tablet Manufacturing Process, J. Pharm. Innovation, 10, 233, 10.1007/s12247-015-9221-x Stadler, P. et al., 2016. Distributed Model Predictive Control for Energy Systems in Microgrids. Mathematics. Suardi, 2016, Explicit MPC: Hard constraint satisfaction under low precision arithmetic, Control Eng. Pract., 47, 60, 10.1016/j.conengprac.2015.12.005 Sutrisno, et al., 2012. Distributed model predictive control and application to irrigation canal. In: Proceedings of 2012 IEEE Conference on Control, Systems & Industrial Informatics (ICCSII 2012), pp. 126–130. Vukov, 2015, Real-time nonlinear MPC and MHE for a large-scale mechatronic application, Control Eng. Pract., 45, 64, 10.1016/j.conengprac.2015.08.012 Wang, 2016, Fuzzy generalized predictive control for nonlinear brushless direct current motor, J. Comput. Nonlinear Dyn., 11 Wang, 2008, Application research of model-predictive control in grain drying process, Drying Technol. Equipment, 6, 267 Wang, 2001, PID autotuner and its application in HVAC systems, Am. Control Conf., 3, 2192, 10.1109/ACC.2001.946075 Wei, 2015, Application of Multivariable Fractional Order PID-MAC in Boiler-turbine Coordinated Control, Process Auto. Instrum., 36 Wolf, 2016, Fast NMPC schemes for regulatory and economic NMPC – A review, J. Process Control, 44, 162, 10.1016/j.jprocont.2016.05.002 Wu, 2008, Automatic canal control system and its operation and design, Adv. Water Sci., 19, 746 Wu, 2014, Design of dynamic matrix control based PID for residual oil outlet temperature in a coke furnace, Chemom. Intell. Lab. Syst., 134, 110, 10.1016/j.chemolab.2014.03.016 Blasco, X., Herrero, J.M., Ramos, C., Sanchis, J., 2007. Model-based predictive control of greenhouse climate for reducing energy and water consumption. Comput. Elect. Agri. 55, 49–70. Xia, 1993, Model algorithmic control for paper machines, Second IEEE Conf. Control Appl., 1, 203 Xu, 2016, Model predictive control of an irrigation canal using dynamic target trajectory, J. Irrig. Drain. Eng., 143, B4016004, 10.1061/(ASCE)IR.1943-4774.0001084 Xu, Z.T. et al., 2013. Greenhouse air temperature predictive control using the dynamic matrix control. In: 4th International Conference on Intelligent Control and Information Processing (ICICIP) Beijing, China, pp. 349–353. Yakub, 2015, Comparative study of autonomous path-following vehicle control via model predictive control and linear quadratic control, Proc. Inst. Mech. Eng. Part D J. Automobile Eng., 229, 1695, 10.1177/0954407014566031 Yan, Z., Wang, J., 2011. Robust model predictive control of nonlinear affine systems based on a two-layer recurrent neural network. In: International Joint Conference on Neural Networks. San Jose, CA, pp. 24–29. Yang, B., Taehyun, S., 2012. Constrained model predictive control for backing-up tractor-trailer system. In: 10th World Congress on Intelligent Control and Automation (WCICA). Beijing, PEOPLES R CHINA, pp. 2165–2170. Yang, Z. et al., 2009. On the single-zone modeling for optimal climate control of a real-sized livestock stable system. In: The 2009 IEEE International Conference on Mechatronics and Automation. Changchum, China, pp. 3849–3854. Zafra-Cabeza, 2011, A hierarchical distributed model predictive control approach to irrigation canals: a risk mitigation perspective, J. Process Control, 21, 787, 10.1016/j.jprocont.2010.12.012 Zafra-Cabeza, A., et al., 2011. Hierarchical Distributed Model Predictive Control for Risk Mitigation: An Irrigation Canal Case Study. In: 2011 American Control Conference, San Francisco, CA, vol. 145 (2). pp. 3172–3177. Zhang, C., Chen, Y., 2011. Applications of DMC-PID Algorithm in the Measurement and Control System for the Greenhouse Environmental Factors. In: 23rd Chinese Control and Decision Conference Mianyang, China, pp. 483–485. Zhang, 2017, Robust model predictive control of the automatic operation boats for aquaculture, Comput. Electron. Agri., 142, 118, 10.1016/j.compag.2017.08.016 Zhang, 2014, Robust distributed model predictive control for uncertain networked control systems, Control Theory & Appl., 8, 1843, 10.1049/iet-cta.2014.0311 Zhang, 2013, Parameters online detection and model predictive control during the grain drying process, Mathematical Problems Eng., 3, 183 Zhang, R. et al., 2015. Distributed Model Predictive Control Based on Nash Optimality for Large Scale Irrigation Systems. In: 9th IFAC Symposium on Advanced Control of Chemical Processes Whistler, CA, vol. 48 (8). pp. 551–555. Zhang, 2017, State space model predictive control for advanced process operation: a review of recent development, new results and insight, Ind. Eng. Chem. Res., 56, 5360, 10.1021/acs.iecr.7b01319 Zhang, 2017, Linear time-varying model predictive controller improving precision of navigation path automatic tracking for agricultural vehicle, Trans. Chinese Soc. Agri. Eng., 33, 104 Zhang, 2009, Controller design for nonlinear systems with time delay using model algorithm control (MAC), Simul. Model. Pract. Theory, 17, 1723, 10.1016/j.simpat.2009.08.005 Zhou, 2014, A distributed parameter model predictive control method for forced air ventilation through stored grain, Appl. Eng. Agric., 30, 593