TY  - CONF
EP  - 2407
T2  - European Control Conference
ID  - eprints435
SP  - 2402
N2  - 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.
M2  - 23th -26th  August 2009
A1  - Bemporad, Alberto
A1  - Muņoz de la Peņa, David
UR  - https://controls.papercept.net/conferences/scripts/abstract.pl?ConfID=5&Number=733
AV  - none
CY  - 23-26 August 2009
TI  - Multiobjective model predictive control based on convex piecewise affine costs
KW  - Predictive control for linear systems; Optimization; Optimization algorithms
Y1  - 2009///
ER  -