Constrained MPC of Uncertain Discrete-Time Markovian Jump Linear Systems
This paper is concerned with constrained model predictive control (MPC) of discrete-time Markovian jump linear systems (MJLSs) subject to polytopic uncertainties in system matrices, where the constraints consist of hard mode-dependent constraints on inputs and states. The multi-step mode-dependent state-feedback control law is utilized to minimize an upper bound on the expected worst-case infinite horizon cost function. To reduce conservatism meanwhile guaranteeing the recursive feasibility, the minimization of the expected worst-case infinite horizon cost function and the constraints handling are dealt with in a separate way. The resulting algorithm is proved to guarantee both the mean square stability and the satisfaction of the hard mode-dependent constraints on inputs and states. Finally, a numerical example is given to illustrate the proposed results.
Constrained MPC discrete-time MJLS polytopic uncertainties Multi-step feedback control law mean square stable
LU Jianbo LI Dewei XI Yugeng
Department of Automation, Shanghai Jiao Tong University, Key Laboratory of System Control and Inform Department of Automation, Shanghai Jiao Tong University,Key Laboratory of System Control and Informa
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
4131-4136
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）