The Estimated Model-based Multirate Control System Robust Stability

Multirate sampled-data control systems is a new control strategy, which is proposed in recent years. As the multirate sampled-data control scheme is to improve system performance, adapt to a variety of complex situations, and many other advantages, multirate control sampled-data systems has been widely used in modern industrial control.This paper deals with the problem of the stability of multirate sampled-data state feedback control systems based on model estimation. In order to enlarge sampling periods while keep the system stable, a plant model was proposed, which has a similar structure to the actual plant. The plant model state is updated at sampling time by the plant's state and the plant model is used to estimate the plant state at sampling intervals. The state feedback control signal is generated base on the model state.Utilizing statistical knowledge of sampling periods and probability asymptotic stability theory, the new stability criterion was proposed. The criterion indicates that the length of sampling periods and their corresponding occurrence frequency affect the stability of system.The proposed criterion gives a tolerance bound for long sampling periods. Since the occurrence frequency of sampling periods was taken into consideration, the proposed criterion gave a more general result than the existing ones.Simulating and analyzing the uniform sampled-data control systems, certainty multirate sampled-data control systems and the multirate sampled-data control systems affected by systems themselves uncertainties and external influences by MATLAB. The results indicates that the method of model estimation is effective and the new stability criterion is less conservative. The last , Simulating and analyzing the effect of model estimation errors to the stability of systems.