Title :
Model predictive control for continuous-time Markov Jump Linear Systems
Author :
Gu Xinxin ; Wen Jiwei ; Peng Li
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
Abstract :
This paper mainly studies the continuous-time Markov Jump Linear Systems (MJLSs) problem based on model predictive control (MPC). Sufficient conditions of the optimization problem, which could guarantee the mean square stability of the close-loop MJLS, are given at every sample time. Since the MPC strategy is aggregated into continuous-time MJLSs, a discrete-time controller is employed to deal with a continuous-time plant and the adopted cost function not only refers to the knowledge of system state but also considers the sampling period. In addition, the feasibility of MPC scheme and the mean square stability of the MJLS are deeply discussed by using the invariant ellipsoid. Finally, the main results are verified by a numerical example.
Keywords :
Markov processes; closed loop systems; continuous time systems; discrete time systems; linear systems; optimisation; predictive control; stability; stochastic systems; MPC strategy; close-loop MJLS; continuous-time MJLS; continuous-time Markov jump linear systems; continuous-time plant; cost function; discrete-time controller; invariant ellipsoid; mean square stability; model predictive control; optimization problem; sampling period; sufficient conditions; system state; Ellipsoids; Linear systems; Markov processes; Optimization; Predictive control; Robustness; Stability analysis; Continuous-time Markov jump linear systems; Invariant ellipsoid; Model predictive control;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7162262
