Study On Networked Predictive Control For Serially Connected Systems

In recent years, model predictive control(MPC) is favored by scholars in academy and industry for its successful application in industrial processes and the enormous economic benefits it brings. It is a hot topic to apply theory of model predictive control to study and solve control, dynamic optimization, and boundary constraint problems for serially connected system, and it has received a lot of beautiful theoretical results and achieved good effects in practical applications. With the application of computer technology, the traditional control systems are replaced by distributed control systems, and the distributed control problem for serially connec-ted systems in which communications between subsystems are delayed has made certain achievements. In this paper, based on existing results, the networked predictive control problem is studied for serially connected systems with time-varying delay.Firstly, for serially connected systems in which communications between subsys-tems are through network, under the condition that there exists time-varying delay in the communications between subsystems. The predictive control model is established and a networked predictive control strategy is proposed based on cooperation. Secondly, the performance index is optimized, the optimal control sequence in a time-domain is obtained, and approaches for designing a controller and a control algorithm are presented. Finally, the stability of the closed-loop system is analyzed, a necessary and sufficient condition of asymptotic stability is obtained for serially connected systems in which communications between subsystems have time-varying delay. The effectiveness of the proposed method is illustrated by the simulation result of a numerical example.