The research of optimization of electric motor speed control based on an improved particle swarm algorithm for upper limb rehabilitation robot

Abstract

To improve the stability of motor operation in upper limb rehabilitation robots, a method for tuning parameters of the sliding mode control (SMC) based on an improved particle swarm optimization algorithm has been proposed, and the output effect of the optimized control system has been simulated and validated. This paper designed a simulation model of the joint motor for an upper-limb rehabilitation robot based on a sliding-mode controller. At the same time, the traditional particle swarm optimization algorithm has been improved to optimize the parameters of the sliding-mode controller, enabling stable operation of the joint motor. In an environment with external disturbances, MATLAB software has been used to simulate the tracking error of motor speed and compare the response speeds and the capabilities of disturbance rejection from different control systems. Compared with the traditional PID, sliding mode control, and the improved sliding mode control systems, the improved sliding mode system which optimized by the improved particle swarm algorithm exhibits a faster response, greater disturbance rejection capability, reduces motor speed tracking error, and significantly enhances the effectiveness of upper limb rehabilitation training.