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Multiobjective model predictive control based on convex piecewise affine costs

Bemporad, Alberto and Muñoz de la Peña, David Multiobjective model predictive control based on convex piecewise affine costs. In: European Control Conference, Budapest, Hungary, 23th -26th August 2009 pp. 2402-2407. (2009)

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This paper proposes a novel model predictive control (MPC) scheme based on multiobjective optimization. At each sampling time, the MPC control action is chosen among the set of Pareto optimal solutions based on a time-varying and state-dependent decision criterion. After recasting the optimization problem associated with the multiobjective MPC controller as a multiparametric multiobjective linear problem, we show that it is possible to compute each Pareto optimal solution as an explicit piecewise affine function of the state vector and of the vector of weights to be assigned to the different objectives in order to get that particular Pareto optimal solution. Furthermore, we provide conditions for selecting Pareto optimal solutions so that the MPC control loop is asymptotically stable, and show the effectiveness of the approach in simulation examples.

Item Type: Conference or Workshop Item (Paper)
Funders: The European Control Conference (ECC)
Uncontrolled Keywords: Predictive control for linear systems; Optimization; Optimization algorithms
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Research Area: Computer Science and Applications
Depositing User: Professor Alberto Bemporad
Date Deposited: 27 Jul 2011 08:34
Last Modified: 17 Nov 2011 14:32
URI: http://eprints.imtlucca.it/id/eprint/435

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