Fast model predictive control for linear periodic systems with state and control constraints. (20th February 2017)

• Record Type: Journal Article
• Authors: Nguyen, Hoai‐Nam; Bourdais, Romain; Gutman, Per‐Olof
• Is Part Of: International journal of robust and nonlinear control. Volume 27:Number 17(2017)
• Page Start: 3703
• Page End: 3726
• Publication Date: 2017-02-20
• Subjects: polyhedral invariant sets -- periodic systems -- model predictive control -- interpolating control -- input and state constraints; Automatic control -- Periodicals; Control theory -- Periodicals; Nonlinear systems -- Periodicals; 629.836
• DOI: 10.1002/rnc.3760
• Languages: English
• ISSNs: 1049-8923

Abstract

Summary: 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. Copyright © 2017 John Wiley & Sons, Ltd.