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Article Dans Une Revue International Journal of Robust and Nonlinear Control Année : 2017

Fast model predictive control for linear periodic systems with state and control constraints

Résumé

The design of stabilizing model predictive control laws for discrete-time linear periodic systems with state and control constraints is considered. Two algorithms are presented. The first one is based on interpolation between several unconstrained periodic controllers. Among them, one controller is chosen for the performance while the rest are used to extend the domain of attraction. The second algorithm aims to improve the performance by combining model predictive control and interpolating control. The proposed approaches not only guarantee recursive feasibility and asymptotic stability but also are optimal for states near the origin.
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Dates et versions

hal-01513720 , version 1 (25-04-2017)

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Hoaï-Nam Nguyen, Romain Bourdais, Per-Olof Gutman. Fast model predictive control for linear periodic systems with state and control constraints. International Journal of Robust and Nonlinear Control, 2017, 27 (17), pp.3703-3726. ⟨10.1002/rnc.3760⟩. ⟨hal-01513720⟩
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