Robust model predictive control for switched linear systems

• Published in: ISA transactions 2019-06, Vol.89, p.1-11
• Main Authors: Sindareh Esfahani, Peyman, Pieper, Jeffrey Kurt
• Format: Article
• Language: English
• Subjects: Linear fractional transformation; Linear matrix inequality; Robust model predictive control; Switched linear systems
• ISSN: 0019-0578; 1879-2022
• DOI: 10.1016/j.isatra.2018.12.006

Developed is a robust model predictive control scheme for a class of discrete-time switched linear systems. The system is described in linear fractional transformation form in the presence of model uncertainty and induced norm bounded disturbances. The objective is to minimize the upper bound of an infinite horizon cost function subject to a terminal inequality. A Lyapunov function analysis for the switched system shows guaranteed closed-loop stability. Taking into account the switching structure of the system, the predictive control design problem along with sufficient conditions for the existence of a solution is expressed in terms of Riccati–Metzler inequalities. Then, these inequalities are turned into a linear matrix inequality feasibility problem. Three cases are analyzed to demonstrate the performance and effectiveness of the proposed robust model predictive controller for switched discrete-time linear systems. •Proposed is a robust model predictive control scheme for a class of discrete-time switched linear systems.•The objective is to minimize an upper bound of a cost function subjected to a terminal inequality.•An arbitrary min-type switch function is considered and multiple switched Lyapunov function is used to proof asymptotic stability.•Studying different aspects of the proposed controller through three comprehensive examples.