Switching Model Predictive Control of Switched Linear Systems with Average Dwell Time
Date of Original Version
In this paper, we address the switching model predictive control (sMPC) problem for a class of switched linear systems with average dwell time (ADT) switching logics. A novel state-feedback switching control synthesis scheme is proposed, such that (i) the sMPC design, subject to ADT switching as well as input and output constraints, can be characterized as an optimization problem of the "worst-case" objective function over infinite moving horizon; (ii) the associated optimal switching control synthesis conditions can be fully formulated as linear matrix inequalities (LMIs), which can be solved efficiently via online convex optimization; and (iii) asymptotic stability of the resulting switched closed-loop system can be proved rigorously using multiple Lyapunov functions. A numerical example has been used to demonstrate effectiveness of the proposed approach.
Proceedings of the American Control Conference
Yuan, Chengzhi, Yan Gu, Wei Zeng, and Paolo Stegagno. "Switching Model Predictive Control of Switched Linear Systems with Average Dwell Time." Proceedings of the American Control Conference 2020-July, (2020): 2888-2893. doi:10.23919/ACC45564.2020.9147362.