volume | PIER Journals

Abstract

To improve the electromagnetic operating stability and dynamic response of a permanent magnet synchronous motor (PMSM) speed control system under load disturbances and speed variations, an improved particle swarm optimization-based super-twisting active disturbance rejection control (IPSO-ISTA-ADRC) method is proposed. Focusing on the speed control loop, high-order power terms are introduced into the super-twisting control law within the ADRC framework to accelerate error convergence. A dynamic boundary-layer function is employed to smooth the switching terms and reduce chattering. In addition, a sigmoid function is incorporated into the extended state observer to improve disturbance estimation and compensation, while an improved particle swarm optimization algorithm is used to optimize the controller parameters. The proposed method is further applied to a sensorless PMSM speed control system to evaluate its control performance under sensorless operating conditions. Simulation results show that, compared with PI, LADRC, and boundary-layer-based STA-ADRC, the proposed method effectively suppresses speed overshoot and fluctuations and shortens the recovery time under no-load startup, load disturbance, and speed variation conditions, thereby achieving improved disturbance rejection, faster dynamic response, and enhanced robustness.

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Dr. Dehai Chen

Mr. Ruilong Liu