Finite time speed control of permanent magnet synchronous motor with variable load based on feedback-error learning

YE Lei，WU Gen-zhong，CHEN Qiang

（College of Information Engineering，Zhejiang University of Technology，Hangzhou 310023，China）

Abstract：Aiming at improving the speed tracking performance and reducing the effect caused by mismatching parameters of proportion integral（PI）controllers when wide range of speed and variable load were considered in traditional permanent magnet synchronous motor（PMSM）speed control system，a finite time speed control approach was proposed based on feedback error learning structure. After the analysis of the motion equation of PMSM，the speed controller was established by combining with a nonlinear PI（NPI）controller in parallel with a radial basis function neural network（RBFNN）controller. The former was provided to guarantee system convergence and stability，and its output was used to update the NN parameters. The adaption laws of NN parameters were designed based on terminal sliding mode（TSM）principle to accelerate the parameters convergence speed. Then，output of the RBFNN controller can gradually replace that of the nonlinear PI controller. The stypticity of the controller was analyzed based on Lyapunov，and it was simulated on PMSM speed control system. The results indicate that the proposed finite time speed control approach which based on feedback error learning structure can reduce the static system error and chattering，and have strong anti-disturbance ability.

Key words：permanent magnet synchronous motor（PMSM）；terminal sliding mode（TSM）；radial basis function neural network