Model predictive control: Recent developments and future promise
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Adetola, 2009, Adaptive model predictive control for constrained nonlinear systems, Systems & Control Letters, 58, 320, 10.1016/j.sysconle.2008.12.002
Aguilera, 2013, Stability analysis of quadratic MPC with a discrete input alphabet, IEEE Transactions on Automatic Control, 58, 3190, 10.1109/TAC.2013.2264551
Alessio, Alessandro, & Bemporad, Alberto (2008). A survey on explicit model predictive control. In Lalo Magni (Ed.), Proceedings of international workshop on assessment and future directions of model predictive control.
Amrit, 2011, Economic optimization using model predictive control with a terminal cost, Annual Reviews in Control, 35, 178, 10.1016/j.arcontrol.2011.10.011
Angeli, 2012, On average performance and stability of economic model predictive control, IEEE Transactions on Automatic Control, 57, 1615, 10.1109/TAC.2011.2179349
Bayer, Florian, Bürger, Mathias, & Allgöwer, Frank (2013). Discrete-time incremental ISS: a framework for robust NMPC. In Proceedings of European control conference, Zurich, Switzerland, July (pp. 2068–2073).
Bemporad, A. (2004). Hybrid toolbox–user’s guide.http://csa.lab.imtlucca.it/~bemporad/hybrid/toolbox.
Bemporad, 2012, Dynamic option hedging via stochastic model predictive control based on scenario simulation, Quantitative Finance, 1
Bemporad, 1999, Control of systems integrating logic, dynamics, and constraints, Automatica, 35, 407, 10.1016/S0005-1098(98)00178-2
Bemporad, 2002, The explicit linear quadratic regulator for constrained systems, Automatica, 38, 3, 10.1016/S0005-1098(01)00174-1
Bemporad, 2011, Ultra-fast stabilizing model predictive control via canonical piecewise affine approximations, IEEE Transactions on Automatic Control, 53, 2209
Bemporad, 2004, Anti wind-up synthesis via sampled-data piecewise affine optimal control, Automatica, 40, 549, 10.1016/j.automatica.2003.11.004
Bernardini, 2009, Scenario-based model predictive control of stochastic constrained linear systems, 6333
Bertsekas, 1971, On the minimax reachability of target sets and target tubes, Automatica, 7, 233, 10.1016/0005-1098(71)90066-5
Bertsekas, 1971, Recursive state estimation for a set-membership description of uncertainty, IEEE Transactions on Automatic Control, 16, 117, 10.1109/TAC.1971.1099674
Biegler, 2013, A survey on sensitivity-based nonlinear model predictive control, 499
Binder, 2001, Introduction to model based optimization of chemical processes on moving horizons, 295
Bryson, 1969
Calafiore, 2006, The scenario approach to robust control design, IEEE Transactions on Automatic Control, 51, 742, 10.1109/TAC.2006.875041
Calafiore, 2013, Robust model predictive control via scenario optimization, IEEE Transactions on Automatic Control, 56, 219, 10.1109/TAC.2012.2203054
Camacho, 2013
Camacho, 2010, Model predictive control techniques for hybrid systems, Annual Reviews in Control, 34, 21, 10.1016/j.arcontrol.2010.02.002
Cannon, 2009, Probabilistic tubes in linear stochastic model predictive control, Systems & Control Letters, 58, 747, 10.1016/j.sysconle.2009.08.004
Cannon, 2009, Probabilistic constrained MPC for multiplicative and additive stochastic uncertainty, IEEE Transactions on Automatic Control, 54, 1626, 10.1109/TAC.2009.2017970
Carrasco, 2011, Feedforward model predictive control, Annual Reviews in Control, 35, 199, 10.1016/j.arcontrol.2011.10.007
Chatterjee, 2011, Stochastic receding horizon control with bounded control inputs: a vector space approach, IEEE Transactions on Automatic Control, 56, 2704, 10.1109/TAC.2011.2159422
Chen, 2012, Distributed economic MPC: application to a nonlinear chemical process network, Journal of Process Control, 22, 689, 10.1016/j.jprocont.2012.01.016
Chisci, 2001, Systems with persistent disturbances: predictive control with restricted constraints, Automatica, 37, 1019, 10.1016/S0005-1098(01)00051-6
Chisci, 2003, Dual mode predictive tracking of piecewise constant references for constrained linear systems, International Journal of Control, 76, 61, 10.1080/0020717021000049160
Christofides, 2013, Distributed model predictive control: a tutorial review and future research directions, Computers & Chemical Engineering, 51, 21, 10.1016/j.compchemeng.2012.05.011
Copp, David, & Hespanha, João Pedro (2014a). Nonlinear output-feedback model predictive control with moving horizon estimation. In Proceedings of the 53rd IEEE conference on decision and control, December.
Copp, 2014
Di Cairano, 2010, Model predictive control tuning by controller matching, IEEE Transactions on Automatic Control, 55, 185, 10.1109/TAC.2009.2033838
Diehl, 2011, A Lyapunov function for economic optimizing model predictive control, IEEE Transactions on Automatic Control, 56, 703, 10.1109/TAC.2010.2101291
Diehl, 2009, Efficient numerical methods for nonlinear MPC and moving horizon estimation, Vol. 384, 391
Domahidi, A., Chu, E., & Boyd, S. (2013). ECOS: an SOCP solver for embedded systems. In Proceedings of the European control conference, Zurich, Switzerland.
Dunbar, 2006, Distributed receding horizon contol for multi-vehicle formation stabilization, Automatica, 42, 549, 10.1016/j.automatica.2005.12.008
Fagiano, Lorenzo, & Teel, Andrew R. (2012). On generalised terminal state constraints for model predictive control. In Proceedings of 4th IFAC nonlinear model predictive control conference (pp. 299–304).
Fagiano, 2013, Generalized terminal state constraint for model predictive control, Automatica, 49, 2622, 10.1016/j.automatica.2013.05.019
Falugi, 2013, Model predictive control for tracking random references, 518
Falugi, 2013, Model predictive control for tracking random references, 518
Falugi, 2014, Getting robustness against unstructured uncertainty: a tube-based MPC approach, IEEE Transactions on Automatic Control, 10.1109/TAC.2013.2287727
Farina, Marcello, & Scattolini, Riccardo (2011). Distributed non-cooperative MPC with neighbour-to-neighbour communication. In Proceedings of the 18th IFAC world congress, Milan, Italy.
Findeisen, 2003, State and output feedback nonlinear model predictive control: an overview, European Journal of Control, 9, 190, 10.3166/ejc.9.190-206
Franco, 2008, Cooperative constrained control of distributed agents with nonlinear dynamics and delayed information exchange: a stabilizing receding-horizon approach, IEEE Transactions on Automatic Control, 53, 324, 10.1109/TAC.2007.914956
Gilbert, 1999, Fast reference governors for systems with state and control constraints and disturbance inputs, International Journal of Robust and Nonlinear Control, 9, 1117, 10.1002/(SICI)1099-1239(19991230)9:15<1117::AID-RNC447>3.0.CO;2-I
Goebel, 2009, Hybrid dynamical systems, IEEE Control Systems Magazine, 29, 28, 10.1109/MCS.2008.931718
Goodwin, 2013, Scenario based closed loop model predictive control with applications to emergency vehicle scheduling, International Journal of Control, 86, 1338, 10.1080/00207179.2013.788215
Goulart, 2006, Optimization over state feedback policies for robust control with constraints, Automatica, 42, 523, 10.1016/j.automatica.2005.08.023
Grimm, 2004, Examples when nonlinear model predictive control is nonrobust, Automatica, 40, 1729, 10.1016/j.automatica.2004.04.014
Grimm, 2007, Nominally robust model predictive control with state constraints, IEEE Transactions on Automatic Control, 52, 1856, 10.1109/TAC.2007.906187
Grüne, Lars (2012). NMPC without terminal constraints. In Proceedings of IFAC conference on nonlinear model predictive control 2012, August.
Grüne, 2013, Economic receding horizon control without terminal constraints, Automatica, 49, 725, 10.1016/j.automatica.2012.12.003
Grüne, 2011
Hartley, E. N., & Maciejowski, J. M. (2009). Initial tuning of predictive controllers by reverse engineering. In Proceedings of European control conference, Budapest, Hungary (pp. 725–730).
Haseltine, 2005, Critical evaluation of extended Kalman filtering and moving-horizon estimation, Industrial & Engineering Chemistry Research, 44, 2451, 10.1021/ie034308l
Hespanha, 2002, Switching between stabilizing controllers, Automatica, 38, 1905, 10.1016/S0005-1098(02)00139-5
Hokayem, 2009, On stochastic receding horizon control with bounded control inputs, 6359
Hokayem, Peter, Chatterjee, Debasish, Ramponi, Federico, Chaloulos, Georgios, & Lygeros, John (2010). Stable stochastic receding horizon control of linear systems with bounded control inputs. In Int. symposium on mathematical theory of networks and systems, MTNS (pp. 31–36).
Houska, 2011, ACOD toolkit—an open-source framework for automatic control and dynamic optimization, Optimal Control Applications and Methods, 10.1002/oca.939
Imsland, 2003, A note on stability, robustness and performance of output feedback nonlinear model predictive control, Journal of Process Control, 13, 633, 10.1016/S0959-1524(03)00006-4
Ji, 2013
Jiang, 2001, Input-to-state stability for discrete-time nonlinear systems, Automatica, 37, 857, 10.1016/S0005-1098(01)00028-0
Jones, 2014, Approximate receding horizon control
Jones, 2007, Multiparametric linear programming with applications in control, European Journal of Control, 13, 152, 10.3166/ejc.13.152-170
Jones, C., & Morari, M. (2006). Multiparametric linear complementarity problems. In Proceedings 45th IEEE conference on decision and control, San Diego, California, USA (pp. 5687–5692).
Kantas, 2009, Sequential Monte Carlo for model predictive control, 263
Kellet, 2004, Smooth Lyapunov functions and robustness of stability for difference inclusions, Systems & Control Letters, 52, 395, 10.1016/j.sysconle.2004.02.015
Kerrigan, Eric C., Jerez, Juan L., Longo, Stephano, & Constantinides, George A. (2013). Number representation in predictive control. In Proceedings of European control conference, Zurich, Switzerland (pp. 60–67).
Kerrigan, 2004, Feedback min–max model predictive control using a single linear program: robust stability and the explicit solution, International Journal of Robust and Nonlinear Control, 14, 395, 10.1002/rnc.889
Keviczky, 2004, A study on decentralized receding horizon control for decoupled systems, 4921
Khalil, 2002
Kirches, 2010, Block structured quadratic programming for the direct multiple shooting method for optimal control, Optimization Methods & Software, 26, 239, 10.1080/10556781003623891
Kolmanovsky, 1998, Theory and computation of disturbance invariant sets for discrete-time linear systems, Mathematical Problems in Engineering, 4, 317, 10.1155/S1024123X98000866
Korda, Milan, & Jones, Colin (2014). Certification of fixed computation time first-order optimization-based controllers for a class on nonlinear dynamics. In Proceedings of the 2014 American control conference.
Kouvaritakis, 2010, Explicit use of probabilistic distributions in linear predictive control, Automatica, 46, 1719, 10.1016/j.automatica.2010.06.034
Kurzhanski, 1993, On the theory of trajectory tubes: a mathematical formalism for uncertain dynamics, viability and control, Vol. 17, 122
Kvasnica, M., Grieder, P., & Baotić, M. (2006). Multi Parametric Toolbox (MPT), http://control.ee.ethz.ch/~mpt/.
Kwon, 2005
Lazar, 2006
Lazar, 2009, Lyapunov functions, stability and input-to-state stability subtleties for discrete-time discontinuous systems, IEEE Transactions on Automatic Control, 51, 2421, 10.1109/TAC.2009.2029297
Lazar, 2013, Further input-to-state stability subleties for discrete-time systems, IEEE Transactions on Automatic Control, 58, 1609, 10.1109/TAC.2012.2231611
Lazar, 2006, Stabilizing model predictive control of hybrid systems, IEEE Transactions on Automatic Control, 51, 1813, 10.1109/TAC.2006.883059
Lazar, 2008, On input-to-state stability of min–max nonlinear model predictive control, Systems & Control Letters, 57, 39, 10.1016/j.sysconle.2007.06.013
Lee, S., Polak, E., & Walrand, J. (2013). A receding horizon control law for harbor defense. In Proceedings of 51st annual Allerton conference on appled optimization theory, Monticello, Illinois, October (pp. 70–77).
Limon, 2009, Input-to-state stability: an unifying framework for robust model predictive control, Vol. 384, 1
Limon, 2006, Input to state stability of min–max MPC controllers for nonlinear systems with bounded uncertainties, Automatica, 42, 797, 10.1016/j.automatica.2006.01.001
Limon, 2006, On the stability of constrained MPC without terminal constraint, IEEE Transactions on Automatic Control, 51, 832, 10.1109/TAC.2006.875014
Limon, 2008, MPC for tracking piecewise constant references for constrained linear systems, Automatica, 2382, 10.1016/j.automatica.2008.01.023
Limon, 2010, Robust tube-based MPC for tracking of constrained linear systems with additive disturbances, Journal of Process Control, 20, 248, 10.1016/j.jprocont.2009.11.007
Liu, 2010, Sequential and iterative architectures for distributed model predictive control of nonlinear process systems, AIChE Journal, 56, 2137, 10.1002/aic.12155
Liu, 2009, Distributed model predictive control of nonlinear process systems, AIChE Journal, 55, 1171, 10.1002/aic.11801
Lofberg, 2003, Approximations of closed-loop minimax MPC, 1438
Løvaas, 2008, Robust output feedback model predictive control for systems with unstructured uncertainty, Automatica, 44, 1933, 10.1016/j.automatica.2007.10.003
Maciejowski, 2002
Maeder, 2009, Linear offset-free model predictive control, Automatica, 45, 2214, 10.1016/j.automatica.2009.06.005
Maeder, 2010, Offset-free reference tracking with model predictive control, Automatica, 46, 1469, 10.1016/j.automatica.2010.05.023
Maestre, 2011, Distributed model predictive control based on a cooperative game, Optimal Control Applications and Methods, 32, 153, 10.1002/oca.940
Maestre, 2014, Vol. 69
Magni, 2001, Output feedback and tracking of nonlinear systems with model predictive control, Automatica, 37
Magni, 2008, Switched model predictive control for performance enhancement, International Journal of Control, 81, 1859, 10.1080/00207170801910417
Marafiore, 2013, Persistently exciting model predictive control, International Journal of Adaptive Control and Signal Processing
Marruedo, D. Limon, Alamo, T., & Camacho, E. F. (2002). Input-to-state stable MPC for constrained discrete-time nonlinear systems with bounded additive uncertainties. In Proceedings of 41st IEEE conference on decision and control, Los Vegas, December (pp. 4619–4624).
Mayne, 2013, An apologia for stabilising conditions in model predictive control, International Journal of Control, 86, 2090, 10.1080/00207179.2013.813647
Mayne, 2011, Tube based robust nonlinear model predictive control, International Journal of Robust and Nonlinear Control, 21, 1341, 10.1002/rnc.1758
Mayne, 2001, Robustifying model predictive control of constrained linear systems, Electronics Letters, 37, 1422, 10.1049/el:20010951
Mayne, 2003, Model predictive control of constrained piecewise affine discrete-time systems, International Journal of Robust and Nonlinear Control, 13, 261, 10.1002/rnc.817
Mayne, 2006, Robust output feedback model predictive control of constrained linear systems, Automatica, 42, 1217, 10.1016/j.automatica.2006.03.005
Mayne, D. Q., Rakovíc, S. V., & Kerrigan, E. C. (2007). Optimal control and piecewise parametric programming. In Proceedings of the European control conference 2007, Kos, Greece, July 2–5 (pp. 2762–2767).
Mayne, 2000, Constrained model predictive control: stability and optimality, Automatica, 36, 789, 10.1016/S0005-1098(99)00214-9
Mayne, 2005, Robust model predictive control of constrained linear systems with bounded disturbances, Automatica, 41, 219, 10.1016/j.automatica.2004.08.019
Müller, 2013, Economic model predictive control with self-tuning terminal cost, European Journal of Control, 19, 408, 10.1016/j.ejcon.2013.05.019
Müller, M. A., Angeli, D., & Allgower, F. (2013b). On convergence of averagely constained economic MPC and necessity of disspativity for optimal steady-state operation. In Proceedings of 2013 American control conference (pp. 3141–3146).
Müller, 2012, Improving performance in model predictive control: switching cost functionals under average dwell-time, Automatica, 48, 402, 10.1016/j.automatica.2011.11.005
Müller, 2012, Model predictive control of switched nonlinear systems under average dwell-time, Journal of Process Control, 22, 1702, 10.1016/j.jprocont.2012.07.004
Muller, 2011, How good is quantized model predictive control with horizon one?, IEEE Transactions on Automatic Control, 56, 2623, 10.1109/TAC.2011.2122610
Müller, 2012, Cooperative control of dynamically decoupled systems via distributed model predictive control, International Journal of Robust and Nonlinear Control, 22, 1376, 10.1002/rnc.2826
Müller, 2012, Robust cooperative control of dynamically decoupled systems via distributed MPC, 412
Muske, 2002, Disturbance modeling for offset-free linear model predictive control, Journal of Process Control, 12, 617, 10.1016/S0959-1524(01)00051-8
Nesterov, 2004, Vol. 87
Pannocchia, 2005, Offset-free receding horizon control of constrained linear systems, AIChE Journal, 51, 3134, 10.1002/aic.10626
Pannocchia, 2003, Disturbance models for offset-free model predictive control, AIChE Journal, 49, 426, 10.1002/aic.690490213
Pannocchia, 2011, Conditions under which suboptimal nonlinear MPC is inherently robust, Systems & Control Letters, 60, 747, 10.1016/j.sysconle.2011.05.013
Patrinos, 2010, A new algorithm for solving convex parametric quadratic programs based on graphical derivatives of solution mappings, Automatica, 46, 1405, 10.1016/j.automatica.2010.06.008
Pin, 2011, Networked predictive control of uncertain constrained nonlinear systems: recursive feasibility and input-to-state stability analysis, IEEE Transactions on Automatic Control, 56, 72, 10.1109/TAC.2010.2051091
Pin, 2009, Robust model predictive control of nonlinear systems with bounded and state-dependent uncertainties, IEEE Transactions on Automatic Control, 64, 1681, 10.1109/TAC.2009.2020641
Polak, 1971
Polak, 2005, On the use of augmented Lagrangians in the solution of generalized semi-infinite min–max problems, Computational Optimization and Applications, 31, 173, 10.1007/s10589-005-2179-8
Primbs, 2007, Portfolio optimization applications of stochastic receding horizon control, 1811
Primbs, 2009, Dynamic hedging of basket options under proportional transaction costs using receding horizon control, International Journal of Control, 82, 1841, 10.1080/00207170902783341
Primbs, 2000, Feasibility and stability of constrained finite receding horizon control, Automatica, 36, 965, 10.1016/S0005-1098(00)00004-2
Primbs, 2008, A stochastic receding horizon control approach to constrained index tracking, Asia-Pacific Financial Markets, 15, 3, 10.1007/s10690-008-9073-1
Primbs, 2009, Stochastic receding horizon control of constrained linear systems with state and control multiplicative noise, IEEE Transactions on Automatic Control, 54, 221, 10.1109/TAC.2008.2010886
Qin, 2003, A survey of industrial model predictive control technology, Control Engineering Practice, 11, 733, 10.1016/S0967-0661(02)00186-7
Quevedo, 2004, Finite constraint set receding horizon quadratic control, International Journal of Robust and Nonlinear Control, 14, 355, 10.1002/rnc.887
Raff, 2007, Nonlinear model predictive control: a passivity-based approach, Vol. 358, 151
Raković, 2012, Invention of prediction structures and categorization of robust MPC syntheses, 245
Raković, 2005, Invariant approximations of the minimal robustly positively invariant sets, IEEE Transactions on Automatic Control, 50, 406, 10.1109/TAC.2005.843854
Rakovic̀, 2012, Parameterized tube model predictive control, IEEE Transactions on Automatic Control, 57, 2746, 10.1109/TAC.2012.2191174
Rao, 2003, Constrained state estimation for nonlinear constrained discrete-time systems: stability and moving horizon approximations, IEEE Transactions on Automatic Control, 48, 246, 10.1109/TAC.2002.808470
Rao, 1998, Application of interior-point methods to model predictive control, Journal of Optimization Theory and Applications, 99, 723, 10.1023/A:1021711402723
Rawlings, 2009, Optimizing process economic performance using model predictive control, Vol. 384, 119
Rawlings, J. B., Angeli, D., & Bates, C. N. (2012). Fundamentals of economic model predictive control. In Proceedings of 51st IEEE conference on decision and control, Maui, Hawaii, December (pp. 3851–3861).
Rawlings, 2008, Unreachable setpoints in model predictive control, IEEE Transactions on Automatic Control, 53, 2209, 10.1109/TAC.2008.928125
Rawlings, 2012, Optimization-based state estimation: current status and some new results, Journal of Process Control, 22, 1439, 10.1016/j.jprocont.2012.03.001
Rawlings, James B., & Mayne, David Q. (2009). Model predictive control: theory and design. Nob Hill, Madison, Wisconsin, August.
Richards, 2007, Robust distributed model predictive control, International Journal of Control, 80, 1517, 10.1080/00207170701491070
Richter, S., Morari, M., & Jones, C. N. (2011). Towards computational complexity certication for constrained MPC based on Lagrange relaxation and the fast gradient method. In Proceedings of the 50th IEEE conference on decision and control and the European control conference, December.
Riggs, Daniel J., & Bitmead, Robert R. (2012). MPC under the hood/sous le capot/unter der Haube. In Proceedings of the 4th IFAC nonlinear model predictive control conference, Noordwijkerhout, Nederland, August.
Rossiter, 1998, A numerically robust state-space approach to stable-predictive control strategies, Automatica, 34, 65, 10.1016/S0005-1098(97)00171-4
Scattolini, 2009, Architectures for distributed and hierarchical model predictive control—a review, Journal of Process Control, 19, 10.1016/j.jprocont.2009.02.003
Scokaert, 1998, Min–max feedback model predictive control for constrained linear systems, IEEE Transactions on Automatic Control, 43, 1136, 10.1109/9.704989
Scokaert, 1999, Suboptimal model predictive control (feasibility implies stability), IEEE Transactions on Automatic Control, 44, 648, 10.1109/9.751369
Seron, Marià M., De Doná, José A., & Goodwin, Graham C. (2000). Global analytical model predictive control with input constraints. In Proceedings of the 39th IEEE conference on decision and control, Sydney, Australia, December (pp. 154–159).
Sha, 2008, A new neural networks based adaptive model predictive control for unknown multiple variable non-linear systems, International Journal of Advanced Mechatronic Systems, 1, 146, 10.1504/IJAMECHS.2008.022013
Sontag, 1995, On the characterization of the input to state stability property, Systems & Control Letters, 24, 351, 10.1016/0167-6911(94)00050-6
Spjøtvold, 2006, On the facet-to-facet property of solutions to convex parametric quadratic programs, Automatica, 42, 2209, 10.1016/j.automatica.2006.06.026
Stewart, 2011, Cooperative distributed model predictive control for nonlinear systems, Journal of Process Control, 21, 698, 10.1016/j.jprocont.2010.11.004
Teel, 2004, Discrete time receding horizon control: is the stability robust?, Vol. 301, 3
Tøndel, 2003, An algorithm for multi-parametric quadratic programming and explicit MPC solutions, Automatica, 39, 489, 10.1016/S0005-1098(02)00250-9
Trodden, P. A., & Richards, A. G. (2007). Robust distributed model predictive control with cooperation. In Proceedings of the European control conference(pp. 2172–2178).
Venkat, A. N., Rawlings, J. B., & Wright, S. J. (2005). Stability and optimality of distributed model predictive control. In Proceedings of 44th IEEE conference on decision and control and the European control conference, Seville, Spain(pp. 6680–6685).
Wächter, 2006, On the implementation of a primal–dual interior point filter line search algorithm for large-scale nonlinear programming, Mathematical Programming, 106, 25, 10.1007/s10107-004-0559-y
Walrand, Jean, Polak, Elijah, & Chung, Hoam (2011). Harbor attack: a pursuit–evasion game. In Proceedings of 49th annual Allerton conference on communication, control and computing, September (pp. 1584–1591).
Wongpiromsarn, 2012, Receding horizon temporal logic planning, IEEE Transactions on Automatic Control, 57, 2817, 10.1109/TAC.2012.2195811
Wright, 1993, Interior point methods for optimal control of discrete-time systems, Journal of Optimization Theory and Applications, 77, 161, 10.1007/BF00940784
Yan, 2005, Incorporating state estimation into model predictive control and its application to network traffic control, Automatica, 41, 595, 10.1016/j.automatica.2004.11.022