Disturbance rejection for systems with measurement noise based on equivalent input disturbance approach and Kalman filter
Unknown disturbances and measurement noise pose a significant challenge to the design of a control system and limit the control performance of the system.This paper proposes a composite control strategy to reduce the impact of measurement noise on disturbance rejection and control performance based on the equivalent input disturbance(EID)approach and Kalman filter(KF).Firstly,a steady-state Kalman filter is designed to remove high-frequency noise from the measurement output.Then,a state observer and an EID estimator are designed using the output of the Kalman filter to calculate an estimate of the equivalent disturbance,and the estimate is used for compensation on the control input channel.Consequently,a composite control law is derived to improve the disturbance rejection performance of the control system with measurement noise.Finally,simulation results of a motion control system were used to demonstrate the validity of the presented method.It reveals that the method enables the system to maintain satisfactory control performance even in the presence of measurement noise and disturbances.
万方数据
维普
