Sliding mode predictive tracking control for DC permanent magnet motor in NCSs with random delay and packet dropouts

Abstract

This paper studies the tracking control of dc permanent magnet motor (DC–PMM) in networked control systems (NCSs) with random delay and packet dropouts in feedback channel (sensor to controller) and the feedforward channel (controller to actuator). A sliding mode predictive tracking control algorithm based on the theory of pseudo partial derivative (PPD) is designed to compensate random delay and packet dropouts in process of motor control. The stability of the proposed method and the convergence of the tracking error are analyzed and proved. Finally, an example about dc motor in NCS is given to verify the effectiveness of the proposed method. Simulation results show that the outputs of dc motor can better track the desired trajectory after compensating by the presented method, and are quite stable.