Sliding Mode Active Disturbance Rejection Control of Permanent Magnet Synchronous Motor Based on Improved Genetic Algorithm

Abstract

Sliding mode control has been widely used to control permanent magnet synchronous motors (PMSM). However, the parameters of the sliding mode controller are difficult to be tuned, which makes the control performance of PMSM hard to be improved. A nonlinear sliding mode control method that integrated a nonlinear reaching law (NRLSMC) and extended state observer (ESO) is proposed in this paper, whose parameters are tuned by an improved genetic algorithm (IGA). The control performance of the nonlinear reaching law in the nonlinear sliding mode controller is analyzed, whose stability is verified based on the Lyapunov theorem. An extended state observer is integrated into the above controller to further improve the anti-interference capability, and compensate for the observed external disturbance of the system into the speed controller in sliding mode. The optimal parameters of the above sliding mode control are tuned by IGA combined with the system speed loop model. The performance of the proposed controller is numerically simulated in MATLAB/Simulink and verified in a control system rapid control prototype (RCP) experimental platform built based on dSPACE 1202. Numerical simulation and experimental results show that the proposed controller can make the PMSM control system with the advantages of no overshoot, fast response, and strong robustness.