Integrated Predictive Control of PMLSM Current and Velocity Based on ST-SMO

Shenhui Du, Zihao Zhang, Jinsong Wang, Kangtao Wang, Hui Zhao and Zheng Li
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Shenhui Du: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Zihao Zhang: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Jinsong Wang: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Kangtao Wang: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Hui Zhao: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Zheng Li: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China

Energies, 2022, vol. 15, issue 15, 1-21

Abstract: To enhance the control performance of a permanent magnet linear synchronous motor (PMLSM) and to improve its dynamic response performance and steady-state accuracy, a PMLSM model predictive integrated control (MPC) system based on a super-twisting sliding mode observer (ST-SMO) is proposed. According to the mathematical model of a PMLSM, this paper designs a three-step model to predict the comprehensive control correction factor, optimize the prediction speed and current, reduce the response time, and enhance the system’s stability. Meanwhile, in order to solve the problem of the PMLSM’s high dependence on mechanical sensors, the ST-SMO is introduced to observe the rotation speed of PMLSM, which has better tracking performance and observation accuracy than a traditional sliding mode observer (SMO). Finally, the experimental verification is carried out on the PMLSM experimental platform. The software simulation and hardware experiment results show that the control system designed in this paper not only simplifies the overall structure of the system, but it also has better control performance and tracking ability. Compared with traditional control methods and SMO, it has better control performance, stability, and speed-tracking performance.

Keywords: permanent magnet linear synchronous motor; model predictive integrated control; super-twisting sliding mode observer; integrated speed and current control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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