This paper is mainly concerned with the model predictive control （MPC） of networked control systems （NCSs） with uncertain time delay and data packets disorder. The network-induced time delay is described as bounde...This paper is mainly concerned with the model predictive control （MPC） of networked control systems （NCSs） with uncertain time delay and data packets disorder. The network-induced time delay is described as bounded and arbitrary process. For the usual state feedback controller, by considering all the possibilities of delays, an augmented state space model of the closed-loop system, which characterizes all the delay cases, is obtained. The stability conditions are given according to the Lyapunov method based on this augmented model. The stability property is inherited in MPC which explicitly considers the physical constraints. A numerical example is given to demonstrate the effectiveness of the proposed MPC.展开更多
基金supported by National Nature Science Foundation of China (Nos. 60934007 and 60874046)the Fundamental Research Funds for the Central Universities (Nos. CDJZR10175501 and CDJXS10171101)+4 种基金the Program for New Century Excellent Talents in the University of Chinathe Scientific Research Foundation for Returned Overseas Chinese Scholarsthe State Education Ministry of Chinathe Nature Science Foundation of Chongqing(No. 2008BB2049)the Innovative Talent Training Project, the Third Stage of the "211 Project", Chongqing University (No. S-09108)
文摘This paper is mainly concerned with the model predictive control （MPC） of networked control systems （NCSs） with uncertain time delay and data packets disorder. The network-induced time delay is described as bounded and arbitrary process. For the usual state feedback controller, by considering all the possibilities of delays, an augmented state space model of the closed-loop system, which characterizes all the delay cases, is obtained. The stability conditions are given according to the Lyapunov method based on this augmented model. The stability property is inherited in MPC which explicitly considers the physical constraints. A numerical example is given to demonstrate the effectiveness of the proposed MPC.
