Research Of Predictive Control For Multirate Sampled Systems

This thesis discusses several researches on multi-rate sampled predictive control, which is divided into two parts. The first part is the controller design, which consists of multi-rate predictive control based on the function space model, multi-rate predictive control based on the network model and dual-rate generalized predictive control with constraint; the second part is the performance analysis of multi-rate predictive control systems. The main results are stated as follows:1. An algorithm of multi-rate predictive control based on the function space model is proposed for the problem of wave or vibration among sampling points. The wave or vibration is overcome by the algorithm, which contains dynamic behavior among sampling points. And the closed system is asymptotically stable.2. A class of multi-rate predictive control based on network model is established. Using predictive controller and network delay compensator, a multi-rate predictive control algorithm for the adverse effect caused by network delay is presented, which can compensate network delay and data package dropout. The closed-loop stability is guaranteed by the algorithm.3. Networking multi-rate predictive control algorithm is proposed for the deterministic networked control system with network delay and package dropout. The algorithm is a good combination of networked control system and multi-rate predictive control. The adverse effect caused by network delay can be compensated by predictive output, receding horizon optimization and feedback correction. The stability of the closed-loop system is analyzed using linear matrix inequalities and Lyapunov stability theorem.4. A constrained dual-rate generalized predictive control algorithm using quadratic programming as the receding horizon optimization strategy is presented. Simulation result shows that the calculation is simplified and the dynamic performance is guaranteed. It's a direct and effective algorithm for treating constraint.