Research on control of mining permanent magnet integrated machine based on optimal sliding mode control

Yanhui Xiao; Sen Wang; Nan Chen; Shiyi Ma; Yan Bao; Wanhong Yu; Miao Yang; Kaiying Shang; Zhenhua Zhan

doi:10.1117/12.2675376

25 May 2023 Research on control of mining permanent magnet integrated machine based on optimal sliding mode control

Yanhui Xiao, Sen Wang, Nan Chen, Shiyi Ma, Yan Bao, Wanhong Yu, Miao Yang, Kaiying Shang, Zhenhua Zhan

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126363U (2023) https://doi.org/10.1117/12.2675376
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

The PMSM based full speed control method is an effective way to realize sensorless control of permanent magnet synchronous motor (PMSM), but because of the complex structure of PMSM, high performance requirements, and the existence of nonlinear, strong coupling and other problems, this method can not achieve high-speed operation in the full speed range. To solve these problems, this paper proposes a sensorless control method for PMSM in the full speed range based on adaptive sliding mode control. Firstly, an adaptive sliding mode filter is loaded on the stator resistance to reduce the influence of current component in the sliding mode controller; Then, the stator resistance is estimated according to the stator resistance, torque and speed variation; Finally, the nonlinear mathematical model of the motor is established to estimate the variation of torque and speed. The PMSM sensorless full speed control model is built in Matlab/Simulink. The simulation results show that this method can effectively realize the PMSM sensorless control in the full speed range.

Citation Download Citation

Yanhui Xiao, Sen Wang, Nan Chen, Shiyi Ma, Yan Bao, Wanhong Yu, Miao Yang, Kaiying Shang, and Zhenhua Zhan "Research on control of mining permanent magnet integrated machine based on optimal sliding mode control", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126363U (25 May 2023); https://doi.org/10.1117/12.2675376

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