159 results found
Mayne DQ, Falugi P, 2019, Stabilizing conditions for model predictive control, International Journal of Robust and Nonlinear Control, Vol: 29, Pages: 894-903, ISSN: 1049-8923
Existing stabilizing conditions that use a terminal cost and constraint that, if satisfied, ensure stability and recursive feasibility for deterministic, robust, and stochastic model predictive control are briefly reviewed and analyzed. It is pointed out that these conditions do not cover all situations. Proposals are made to cover a wider range of desired applications.
Mayne DQ, 2018, Competing methods for robust and stochastic MPC, 6th International-Federation-of-Automatic-Control (IFAC) Conference on Nonlinear-Model-Predictive-Control (NMPC), Publisher: ELSEVIER SCIENCE BV, Pages: 169-174, ISSN: 2405-8963
Mayne D, Falugi P, 2015, Generalised stabilizing conditions for model predictive control, Journal of Optimization Theory and Applications, Vol: 169, Pages: 719-734, ISSN: 1573-2878
This note addresses the tracking problem for model predictive control. It presents simple procedures for both linear and nonlinear constrained model predictive control when the desired equilibrium state is any point in a specified set. The resultant region of attraction is the union of the regions of attraction for each equilibrium state in the specified set and is therefore larger than that obtained when conventional model predictive control is employed.
Mayne DQ, 2014, Model predictive control: Recent developments and future promise, AUTOMATICA, Vol: 50, Pages: 2967-2986, ISSN: 0005-1098
Falugi P, Mayne DQ, 2014, Getting Robustness Against Unstructured Uncertainty: A Tube-Based MPC Approach, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 59, Pages: 1290-1295, ISSN: 0018-9286
Goodwin GC, Garrido MEC, Feuer A, et al., 2014, On the use of one bit quantizers in networked control, AUTOMATICA, Vol: 50, Pages: 1122-1127, ISSN: 0005-1098
Cea MG, Goodwin GC, Feuer A, et al., 2014, On the Control Rate versus Quantizer-Resolution Trade Off in Networked Control, 19th World Congress of the International-Federation-of-Automatic-Control (IFAC), Publisher: ELSEVIER SCIENCE BV, Pages: 10343-10348, ISSN: 2405-8963
Falugi P, Mayne DQ, 2013, Tracking a periodic reference using nonlinear model predictive control, IEEE Conference on decision and Control, Pages: 5096-6000, ISSN: 0743-1546
Pannocchia G, Mayne DQ, Rawlings JB, et al., 2013, A parsimonious algorithm for the solution of continuous-time constrained LQR problems with guaranteed convergence, European Control Conference (ECC), Publisher: IEEE, Pages: 1553-1558
Falugi P, Mayne DQ, 2013, Model predictive control for tracking random references, European Control Conference (ECC), Publisher: IEEE, Pages: 518-523
P Falugi, D Q Mayne, 2012, Tracking performance of model predictive control, Proc. 51st IEEE Conference on Decision and Control, Pages: 2631-2636
Mayne DQ, 2011, Personal impressions of the dawn of modern control, ANNUAL REVIEWS IN CONTROL, Vol: 35, Pages: 153-159, ISSN: 1367-5788
Mayne DQ, Kerrigan EC, van Wyk EJ, et al., 2011, Tube-based robust nonlinear model predictive control, International Journal of Robust and Nonlinear Control, Vol: 21, Pages: 1341-1353, ISSN: 1099-1239
This paper extends tube-based model predictive control of linear systems to achieve robust control of nonlinear systems subject to additive disturbances. A central or reference trajectory is determined by solving a nominal optimal control problem. The local linear controller, employed in tube-based robust control of linear systems, is replaced by an ancillary model predictive controller that forces the trajectories of the disturbed system to lie in a tube whose center is the reference trajectory thereby enabling robust control of uncertain nonlinear systems to be achieved.
Mayne DQ, 2011, Jason L. Speyer and David H. Jacobson: Primer on Optimal Control Theory, JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, Vol: 149, Pages: 678-680, ISSN: 0022-3239
Mayne DQ, Kerrigan EC, Falugi P, 2011, Robust model predictive control: Advantages and disadvantages of tube-based methods, Pages: 191-196, ISSN: 1474-6670
An important reason for the success of model predictive control is the fact that, for deterministic systems, feedback and open-loop control are equivalent so that 'optimal' (but implicit) feedback may be obtained by solving an open-loop optimal control problem at each state encountered. This equivalence is not maintained in the presence of uncertainty complicating the development of robust model predictive control. The advantages and limitations of tubebased model predictive control for dealing with uncertainty of various forms are discussed, firstly in the context of constrained linear systems, and an extension to deal with robustness against unstructured uncertainty is briefly described. Tube-based control requires the determination both of a nominal or reference trajectory and an ancillary controller that constrains deviations of the state of the uncertain systems from the nominal trajectory and is difficult to extend to nonlinear systems. A novel ancillary controller for tube-based control of constrained nonlinear systems with additive disturbances that overcomes some disadvantages of a previous version and is relatively simple to implement is described and assessed; the addition of a terminal equality constraint to the nominal optimal control problem and its removal from the ancillary optimal control problem simplifies the analysis, removes some restrictive assumptions, and enables stronger results to be obtained. © 2011 IFAC.
Goodwin GC, Mayne DQ, Chen K-Y, et al., 2010, An introduction to the control of switching electronic systems, ANNUAL REVIEWS IN CONTROL, Vol: 34, Pages: 209-220, ISSN: 1367-5788
Pannocchia G, Rawlings JB, Mayne DQ, et al., 2010, On Computing Solutions to the Continuous Time Constrained Linear Quadratic Regulator, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 55, Pages: 2192-2198, ISSN: 0018-9286
Spjotvold J, Kerrigan EC, Mayne DQ, et al., 2009, Inf-sup control of discontinuous piecewise affine systems, INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Vol: 19, Pages: 1471-1492, ISSN: 1049-8923
Mayne DQ, Rakovic SV, Findeisen R, et al., 2009, Robust output feedback model predictive control of constrained linear systems: Time varying case, 45th IEEE Conference on Decision and Control, Publisher: PERGAMON-ELSEVIER SCIENCE LTD, Pages: 2082-2087, ISSN: 0005-1098
Goodwin GC, Seron MM, Mayne DQ, 2008, Optimization opportunities in mining, metal and mineral processing, ANNUAL REVIEWS IN CONTROL, Vol: 32, Pages: 17-32, ISSN: 1367-5788
Rakovic S V, Kerrigan E C, Kouramas K I, et al., 2007, Optimized robust control invariance for linear discrete-time systems: Theoretical foundations, Automatica, Vol: 43, Pages: 831-841
Mayne DQ, 2007, Personal impressions of the dawn of modern control, EUROPEAN JOURNAL OF CONTROL, Vol: 13, Pages: 61-70, ISSN: 0947-3580
Rakovic SV, Mayne DQ, 2007, Robust model predictive control for obstacle avoidance: Discrete time case, International Workshop on Assessment and Future Directions of Nonlinear Model Predictive Control, Publisher: SPRINGER-VERLAG BERLIN, Pages: 617-627, ISSN: 0170-8643
Mayne DQ, Kerrigan EC, 2007, Tube-based robust nonlinear model predictive control, IFAC Symposium on Nonlinear Control Systems (NOLCOS 2007)
Mayne D Q, Rakovic S V, Findeisen R, et al., 2006, Robust Output Feedback Model Predictive Control for Constrained Linear Systems under Uncertainty Based on Feed Forward and Positive Invariant
Rakovic S V, Teel A R, Mayne D Q, et al., 2006, Simple Robust Control Invariant Tubes for Some Classes of Nonlinear Discrete Time Systems, Pages: 6397-6402
Mayne DQ, Rakovic SV, Findeisen R, et al., 2006, Robust output feedback model predictive control of constrained linear systems, AUTOMATICA, Vol: 42, Pages: 1217-1222, ISSN: 0005-1098
Rakovic SV, Kerrigan EC, Mayne DQ, et al., 2006, Reachability analysis of discrete-time systems with disturbances, IEEE Transactions on Automatic Control, Vol: 51, Pages: 546-561, ISSN: 0018-9286
Mayne DQ, Rakovic SV, Vinter RB, et al., 2006, Characterization of the solution to a constrained H-infinity optimal control problem, AUTOMATICA, Vol: 42, Pages: 371-382, ISSN: 0005-1098
This paper obtains an explicit Solution to a finite horizon min-max optimal control problem where the system is linear and discrete-time with control and state constraints, and the cost quadratic; the disturbance is negatively costed, as in the standard H-infinity problem, and is constrained. The cost is minimized over control policies and maximized over disturbance sequences so that the Solution yields a feedback control. It is shown that, under certain conditions, the value function is piecewise quadratic and the optimal control policy piecewise affine, being quadratic and affine, respectively, in polyhedra that partition the domain of the value function. (C) 2005 Elsevier Ltd. All rights reserved.
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