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Paper TuB3.2

Bemporad, Alberto (University of Siena), Muņoz de la Peņa, David (Universidad de Sevilla)

Multiobjective Model Predictive Control Based on Convex Piecewise Affine Costs

Scheduled for presentation during the Invited Session "Recent Advances on Approximated Explicit Model Predictive Control" (TuB3), Tuesday, August 25, 2009, 14:20−14:40, ROOM I 6

The European Control Conference 2009, August 23-26, 2009, Budapest, Hungary

This information is tentative and subject to change. Compiled on September 17, 2021

Keywords Predictive control for linear systems, Optimization, Optimization algorithms

Abstract

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.

 

 

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