Position control for permanent magnet synchronous motor based on neural network and terminal sliding mode control
Wenwu Zhu, Dongbo Chen, Haibo Du, Xiangyu Wang
Abstract
A finite-time control strategy is proposed to solve the problem of position tracking control for a permanent magnet synchronous motor servo system. It can guarantee that the motor’s desired position can be tracked in a finite time. Firstly, for the d-axis voltage, a first-order finite-time controller is designed based on the vector control principle. Then, for the q-axis voltage, based on a radial basis function (RBF) neural network, an integral high-order terminal sliding mode controller is designed. Theoretical analysis shows that under the proposed controller, the desired position can be tracked by the motor position in a finite time. Simulation results are given to show that the proposed control method has a strong anti-disturbance ability and a fast convergence performance.