volume | PIER Journals

Abstract

The object of this paper is a permanent magnet synchronous linear motor (PMLSM), whose control method is based on a model-referenced adaptive system (MRAS), and it analyses the speed identification of a permanent magnet synchronous linear motor without position sensors. The article proposes a new model-referenced adaptive method, which utilises a sliding-mode variable structure control method (SMC), to replace the PI control algorithm utilised in conventional model-referenced adaptive algorithm. The control system of the PMLSM is therefore designed and studied based on the change of the adaptive law in model-referenced adaption. the mathematical model of the PMLSM itself is chosen as the reference model, and the feedback magnetic chain model of the motor output is chosen as the adjustable model, replacing the conventional current model and simplifying the control algorithm. The sliding mode surface of the sliding mode variable structure control algorithm is constructed using the reference model and the output error of the adjustable model. Through theoretical analysis and simulation models built by MATLAB/Simulink simulation software, the simulation results show that the designed PMLSM speed induction-free control system MRAS speed observer based on the sliding mode variable structure has strong robustness and excellent dynamic static performance. The advantages verified by the new algorithm achieve the experimental purpose of the expected assumptions.

1. Huang, S., T. W. Ching, W. Li, et al. "Overview of linear motors for transportation applications," 2018 IEEE 27th International Symposium on Industrial Electronics (ISIE), 150-154, IEEE, 2018.
doi:10.1109/ISIE.2018.8433682 Google Scholar

2. Wang, H. and J. Leng, "Summary on development of permanent magnet synchronous motor," 2018 Chinese Control And Decision Conference (CCDC), 689-693, IEEE, 2018.
doi:10.1109/CCDC.2018.8407219 Google Scholar

3. Liang, B., Y. Wang, and J. Wei, "A compensation method for rotor position estimation of PMSM based on pulsating high frequency injection," 2020 23rd International Conference on Electrical Machines and Systems (ICEMS), 2128-2132, IEEE, 2020.
doi:10.23919/ICEMS50442.2020.9290785 Google Scholar

4. Wang, G., R. Liu, N. Zhao, et al. "Enhanced linear ADRC strategy for HF pulse voltage signal injection-based sensorless IPMSM drives," IEEE Transactions on Power Electronics, Vol. 34, No. 1, 514-525, 2018.
doi:10.1109/TPEL.2018.2814056 Google Scholar

5. Bin, X., X. Luo, L. Zhu, et al. "Sensorless control of dual three-phase PMSM with high frequency voltage signal injection," 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 1-4, IEEE, 2019. Google Scholar

6. Han, X., Q. Teng, and W. Luo, "Model predictive torque control for PMSM driven by three-level inverter based on extended Kalman filter speed observer," 2018 IEEE International Conference of Intelligent Robotic and Control Engineering (IRCE), 166-170, IEEE, 2018.
doi:10.1109/IRCE.2018.8492971 Google Scholar

7. Tang, H., H. Li, and J. Lin, "Research on sensorless control method of PMSM based on a Kalman filter sliding mode observer," 2018 10th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), 290-293, IEEE, 2018.
doi:10.1109/ICMTMA.2018.00077 Google Scholar

8. Nicola, M. and C. I. Nicola, "Sensorless control of PMSM using fractional order SMC and extended Kalman observer," 2021 18th International Multi-Conference on Systems, Signals & Devices (SSD), 526-532, IEEE, 2021.
doi:10.1109/SSD52085.2021.9429370 Google Scholar

9. Cheema, M. A. M., J. E. Fletcher, M. Farshadnia, et al. "Combined speed and direct thrust force control of linear permanent-magnet synchronous motors with sensorless speed estimation using a sliding-mode control with integral action," IEEE Transactions on Industrial Electronics, Vol. 64, No. 5, 3489-3501, 2017.
doi:10.1109/TIE.2017.2652368 Google Scholar

10. He, L., F. Wang, and D. Ke, "FPGA-based sliding-mode predictive control for PMSM speed regulation system using an adaptive ultralocal model," IEEE Transactions on Power Electronics, Vol. 36, No. 5, 5784-5793, 2020.
doi:10.1109/TPEL.2020.3028545 Google Scholar

11. Wang, H., X. Ge, and Y. C. Liu, "Second-order sliding-mode MRAS observer-based sensorless vector control of linear induction motor drives for medium-low speed maglev applications," IEEE Transactions on Industrial Electronics, Vol. 65, No. 12, 9938-9952, 2018.
doi:10.1109/TIE.2018.2818664 Google Scholar

12. Li, Z., S. Zhou, Y. Xiao, et al. "Sensorless vector control of permanent magnet synchronous linear motor based on self-adaptive super-twisting sliding mode controller," IEEE Access, Vol. 7, 44998-45011, 2019.
doi:10.1109/ACCESS.2019.2909308 Google Scholar

13. Shi, C. and C. Wang, "Sensorless vector control of three-phase permanent magnet synchronous motor based on model reference adaptive system," 2018 IEEE 4th International Conference on Control Science and Systems Engineering (ICCSSE), 178-182, IEEE, 2018. Google Scholar

14. Narayanan, G., "Stator flux based model reference adaptive observers for rotor position and speed estimation in doubly-fed induction machines," 2018 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), 1-6, IEEE, 2018. Google Scholar

15. Elmorshedy, M. F., W. Xu, Y. Liu, et al. "Sensorless direct thrust control of a linear induction motor based on MRAS," 2019 12th International Symposium on Linear Drives for Industry Applications (LDIA), 1-6, IEEE, 2019. Google Scholar

16. Ni, H., B. Ding, F. Zhao, et al. "Adaptive terminal sliding mode control for permanent magnet linear synchronous motor," 2020 IEEE International Conference on High Voltage Engineering and Application (ICHVE), 1-4, IEEE, 2020. Google Scholar

Dr. Mingwei Li

Dr. Kailin Lv

Professor Cheng Wen

Dr. Qiankai Zhao

Dr. Xingqiao Zhao

Dr. Xin Wang