Stability of multirate sampled-data control systems based on model estimation

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 had a similar structure to the actual plant. The state feedback control signal was generated based on the model state that approximated the plant dynamic state. Utilizing probability asymptotic stability theory, a new stability criterion was proposed. The proposed criterion gave 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. Numerical example and simulation results indicated that the method of model estimation was effective and the new stability criterion was less conservative.