Optimal Estimation And Output Feedback Predictive Control For Networked Control Systems

Networked control system is a kind of space distributed control systems. Its subsystems communicate with each other by network. Compared with the traditional control systems, networked control system can realize the information resource sharing and remote control. It has high reliability and strong anti-interference ability. Therefore, network control system has attracted more and more attention from the scholars at home and abroad. It has become a hot topic. But in fact, there are still a lot of problems in the practical industrial process, such as measurement delays, packet losses, wrong order of data packets, constrained condition and so on.Among them, measurement delays, packet losses and constrained condition are commonly seen in networked control system. So this paper pays attentions to how to deal with these problems to get a good control performance. On one hand, we regard packet losses as infinite delays and then build a model. In order to describe delays and packet losses at the same time, we take delays into consideration. Based on the probability distribution of the delays is known, a reorganised innovation analysis approach is used. We propose estimator algorithms based on the statistical properties. On the other hand, we design an output feedback bounded controller based on the Lyapunov function and states observer. Also, a stability region is given. Furthermore, we make the region as a terminal region constraint to get an output feedback predictive controller in order that the states outside the stability region can be controlled into the region.The main result of this paper contains two parts as follows:Firstly, for a class of networked control systems with both random measurement delays and packet dropouts, a optimal estimation method is present. At first, we build a model to describe the phenomenon that delays and packet dropouts exit at the same time. And a novel measurement sequence is redefined. Then we solve the optimal estimation problem on the basis of Riccati equation and modified Kalman filtering formulation. A numerical example is provided to demonstrate the effectiveness of the main result in the last.Secondly, for a class of constrained systems with unavailable state measurements,we present a model predictive control algorithm and description of stability domain based on states observer and Lyapunov function. Then the feasibility of the system is verified. At last, a numerical simulation illustrates the validity of the algorithm.