Parameterized Tube Model Predictive Control

This paper develops a parameterized tube model predictive control (MPC) synthesis method. The most relevant novel feature of our proposal is the online use of a single tractable linear program that optimizes parameterized, Minkowski decomposable, state and control tubes and an associated, fully sepa...

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Vydáno v:	IEEE transactions on automatic control Ročník 57; číslo 11; s. 2746 - 2761
Hlavní autoři:	Rakovic, S. V., Kouvaritakis, B., Cannon, M., Panos, C., Findeisen, R.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY IEEE 01.11.2012 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Adaptative systems Applied sciences Automatic control Computer science; control theory; systems Constrained control Control theory. Systems convex programming Dynamical systems Electron tubes Exact sciences and technology Linearity Mathematical models Nonlinearity Optimal control Optimization Policies Predictive control Proposals robust control Robustness set-dynamics System theory tube model predictive control Tubes set-dynamics Minkowski metric Non linear control Systems theory Affine transformation Convex programming Constrained optimization Robust control tube model predictive control Model predictive control Control constraint Constrained control Feasibility Dynamic programming
ISSN:	0018-9286, 1558-2523
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Abstract	This paper develops a parameterized tube model predictive control (MPC) synthesis method. The most relevant novel feature of our proposal is the online use of a single tractable linear program that optimizes parameterized, Minkowski decomposable, state and control tubes and an associated, fully separable, nonlinear, control policy. The induced control policy enjoys a higher degree of nonlinearity than existing tube MPC and robust MPC using disturbance affine control policy. Our proposal offers greater generality than the state of the art robust MPC methods. It is conjectured, and also established in three cases, that our proposal is equivalent, feasibility-wise, to dynamic programming (DP). It is also shown that, under natural assumptions, our method is computationally efficient while it possesses rather strong system theoretic properties.
AbstractList	This paper develops a parameterized tube model predictive control (MPC) synthesis method. The most relevant novel feature of our proposal is the online use of a single tractable linear program that optimizes parameterized, Minkowski decomposable, state and control tubes and an associated, fully separable, nonlinear, control policy. The induced control policy enjoys a higher degree of nonlinearity than existing tube MPC and robust MPC using disturbance affine control policy. Our proposal offers greater generality than the state of the art robust MPC methods. It is conjectured, and also established in three cases, that our proposal is equivalent, feasibility-wise, to dynamic programming (DP). It is also shown that, under natural assumptions, our method is computationally efficient while it possesses rather strong system theoretic properties.
Author	Rakovic, S. V. Kouvaritakis, B. Cannon, M. Panos, C. Findeisen, R.
Author_xml	– sequence: 1 givenname: S. V. surname: Rakovic fullname: Rakovic, S. V. email: svr@sasavrakovic.com organization: Univ. of Maryland, College Park, MD, USA – sequence: 2 givenname: B. surname: Kouvaritakis fullname: Kouvaritakis, B. email: basil.kouvaritakis@eng.ox.ac.uk organization: Dept. of Eng. Sci., Oxford Univ., Oxford, UK – sequence: 3 givenname: M. surname: Cannon fullname: Cannon, M. email: mark.cannon@eng.ox.ac.uk organization: Dept. of Eng. Sci., Oxford Univ., Oxford, UK – sequence: 4 givenname: C. surname: Panos fullname: Panos, C. email: christos.panos08@ic.ac.uk organization: Dept. of Chem. Eng., Imperial Coll. London, London, UK – sequence: 5 givenname: R. surname: Findeisen fullname: Findeisen, R. email: rolf.findeisen@ovgu.de organization: Syst. Theor. & Control Lab., Otto-von-Guericke-Univ. of Magdeburg, Magdeburg, Germany
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SubjectTerms	Adaptative systems Applied sciences Automatic control Computer science; control theory; systems Constrained control Control theory. Systems convex programming Dynamical systems Electron tubes Exact sciences and technology Linearity Mathematical models Nonlinearity Optimal control Optimization Policies Predictive control Proposals robust control Robustness set-dynamics System theory tube model predictive control Tubes
Title	Parameterized Tube Model Predictive Control
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