volume | PIER Journals

Abstract

To address the problem that the control performance of permanent magnet synchronous motor (PMSM) in model predictive torque control (MPTC) is highly sensitive to motor parameters, an improved model predictive torque control scheme for PMSM based on anti-stagnation particle swarm online parameter identification (ASPSO-IMPTC) is proposed. First, an improved MPTC strategy based on inductance and magnetic chain parameter compensation is proposed. Compared with conventional MPTC, the proposed method can acquire accurate motor parameters in real-time, thereby enhancing both the control performance and parameter robustness of PMSM. Second, a review mechanism is proposed to enhance traditional PSO parameter identification. This method prevents particle swarm stagnation, enhances the parameter identification ability of the traditional method, and improves the real-time accuracy of the motor parameters. The parameter robustness of the motor is further enhanced. Finally, the experimental results show that the proposed ASPSO-IMPTC strategy can effectively improve the control performance and parameter robustness of PMSM when parameters mismatch occurs in PMSM.

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Dr. Yang Zhang

Mr. Ping Yang

Dr. Chenhui Liu

Dr. Sicheng Li

Dr. Kun Cao

Dr. Ziying Liu

Dr. Zhun Cheng