Abstract:For the predictive control strategy of the permanent magnet synchronous motor position servo system, both model predictive direct speed control (MPDSC) and deadbeat predictive speed control (DPSC) depend on an accurate control system model. However, in practical applications, the motor parameters are changing and challenging to measure, which makes the control performance worse. Moreover, the nonlinearity of the inverter will also affect the prediction accuracy and reduce the performance of the control system. Recently, some methods have been proposed to solve the issues of parameter inaccuracy, but most are computationally expensive and hard to implement in practice. This paper proposes a robust deadbeat predictive speed control (R-DPSC) strategy to improve the control performance of the permanent magnet synchronous motor position servo system by incorporating the deadbeat control and the disturbance observer. Firstly, according to the mathematical model of PMSM in the synchronous coordinate frame and the deadbeat control principle, the current and speed loops are designed for the servo drive. A proportional controller is used to design the position loop. Then, according to the discrete-state model of the motor, the reference voltages are predicted and converted into the switching signals of the inverter by space vector pulse-width modulation (SVPWM). In this paper, the incremental model is adopted to predict the current without the permanent-magnet flux value, and an extended state observer (ESO) is designed with the incremental model to estimate and compensate for the prediction errors caused by inaccurate parameters and load disturbance. The R-DPSC strategy combined with ESO can accurately track the desired position in the case of inaccurate parameters and external disturbance in load. In order to reduce the oscillation caused by the observer when the system approaches the given position reference, a prediction error compensation method is proposed, which uses different compensation quantities according to different working states of the system. The R-DPSC strategy with prediction error compensation method (PR-DPSC) can improve the robustness of the system and maintain the good dynamic performance of the DPSC strategy. Thus, the system can achieve better position-tracking performance. The experimental results show that when the control parameters and the load torque settings do not match the actual values, the position tracking error is eliminated by the R-DPSC strategy. After adopting the PR-DPSC strategy, the position tracking error can be eliminated, and the oscillation phenomenon disappears when the actual position is close to the given position. Furthermore, the time for the system to reach the given position is reduced. Under the same experimental conditions, comparative experiments were carried out for different control schemes, which proved that the PR-DPSC strategy has faster position tracking speed and better anti-disturbance performance. The research conclusions are as follows: (1) The proposed DPSC strategy improves the dynamic response of the system, enabling the system to reach a given position faster; (2) The designed ESO can observe the disturbance caused by parameter mismatch, load, and inverter nonlinearity. The proposed compensation strategy eliminates the oscillation phenomenon when the system reaches a given position, and the control accuracy and dynamic performance are improved.
[1] 付兴贺, 江政龙, 吕鸿飞, 等. 电励磁同步电机无刷励磁与转矩密度提升技术发展综述[J]. 电工技术学报, 2022, 37(7): 1689-1702. Fu Xinghe, Jiang Zhenglong, Lü Hongfei, et al.Review of the blushless excitation and torque density improvement in wound field synchronous motors[J]. Transactions of China Electrotechnical Society, 2022, 37(7): 1689-1702. [2] 王一波, 王政, 温从剑, 等. 多通道三电平风力发电系统协同控制策略研究[J]. 中国电机工程学报, 2019, 39(2): 366-375, 634. Wang Yibo, Wang Zheng, Wen Congjian, et al.Collaborative control strategies for multi-channel three-level wind energy conversion system[J]. Pro- ceedings of the CSEE, 2019, 39(2): 366-375, 634. [3] Kazmierkowski M P, Malesani L.Current control techniques for three-phase voltage-source PWM con- verters: a survey[J]. IEEE Transactions on Industrial Electronics, 1998, 45(5): 691-703. [4] 李祥林, 薛志伟, 阎学雨, 等. 基于电压矢量快速筛选的永磁同步电机三矢量模型预测转矩控制[J]. 电工技术学报, 2022, 37(7): 1666-1678. Li Xianglin, Xue Zhiwei, Yan Xueyu, et al.Voltage vector rapid screening-based three-vector model predictive torque control for permanent magnet syn- chronous motor[J]. Transactions of China Electro- technical Society, 2022, 37(7): 1666-1678. [5] 郭磊磊, 王朋帅, 李琰琰, 等. 不同代价函数下永磁同步电机模型预测控制参数失配可视化分析[J]. 电工技术学报, 2023, 38(4): 903-914. Guo Leilei, Wang Pengshuai, Li Yanyan, et al.Visual analysis of parameters mismatch in model predictive control for permanent magnet synchronous motor under different cost functions[J]. Transactions of China Electrotechnical Society, 2023, 38(4): 903-914. [6] 章回炫, 范涛, 边元均, 等. 永磁同步电机高性能电流预测控制[J]. 电工技术学报, 2022, 37(17): 4335-4345. Zhang Huixuan, Fan Tao, Bian Yuanjun, et al.Predictive current control strategy of permanent magnet synchronous motors with high performance[J]. Transactions of China Electrotechnical Society, 2022, 37(17): 4335-4345. [7] 李昱, 郭宏, 平朝春, 等. 基于电流源变流器的永磁同步电机驱动系统全状态变量预测转矩控制[J]. 电工技术学报, 2021, 36(1): 15-26. Li Yu, Guo Hong, Ping Zhaochun, et al.A full-state variable predictive torque control of current source converter fed permanent magnet synchronous motor drives[J]. Transactions of China Electrotechnical Society, 2021, 36(1): 15-26. [8] 谷鑫, 鲁金月, 王志强, 等. 基于无差拍电流预测控制的永磁同步电机谐波电流抑制策略[J]. 电工技术学报, 2022, 37(24): 6345-6356. Gu Xin, Lu Jinyue, Wang Zhiqiang, et al.Harmonic current suppression strategy for permanent magnet synchronous motor based on deadbeat current predi- ction control[J]. Transactions of China Electro- technical Society, 2022, 37(24): 6345-6356. [9] Gu Minrui, Wang Zheng, Yu Kailiang, et al.Inter- leaved model predictive control for three-level neutral- point-clamped dual three-phase PMSM drives with low switching frequencies[J]. IEEE Transactions on Power Electronics, 2021, 36(10): 11618-11630. [10] Kawai H, Zhang Zhenbin, Kennel R, et al.Direct speed control based on finite control set model predictive control with voltage smoother[J]. IEEE Transactions on Industrial Electronics, 2023, 70(3): 2363-2372. [11] Gu Minrui, Wang Zheng, Wen Congjian, et al.Collaborative mid-point voltage regulation in low- switching-frequency MPC for three-level NPC inver- ters fed dual three-phase PMSM drives[J]. IEEE Open Journal of Power Electronics, 2021, 2: 673-682. [12] Yu Kailiang, Wang Zheng, Hua Wei, et al.Robust cascaded deadbeat predictive control for dual three- phase variable-flux PMSM considering intrinsic delay in speed loop[J]. IEEE Transactions on Industrial Electronics, 2022, 69(12): 12107-12118. [13] Yu Kailiang, Wang Zheng.Improved deadbeat predi- ctive current control of dual three-phase variable-flux PMSM drives with composite disturbance observer[J]. IEEE Transactions on Power Electronics, 2022, 37(7): 8310-8321. [14] Kim H S, Lee K.Model predictive current control with online parameter estimation for synchronous reluctance machine controlled by high-frequency signal injection position-sensorless[J]. IEEE Access, 2022, 10: 25267-25277. [15] Wang Kang, Lorenz R D, Baloch N A.Enhanced methodology for injection-based real-time parameter estimation to improve back EMF self-sensing in induction machine deadbeat-direct torque and flux control drives[J]. IEEE Transactions on Industry Applications, 2018, 54(6): 6071-6080. [16] Liu Zhaohua, Wei Hualiang, Li Xiaohua, et al.Global identification of electrical and mechanical parameters in PMSM drive based on dynamic self-learning PSO[J]. IEEE Transactions on Power Electronics, 2018, 33(12): 10858-10871. [17] Zhang Xiaoguang, Cheng Yu, Zhao Zhihao, et al.Robust model predictive direct speed control for SPMSM drives based on full parameter disturbances and load observer[J]. IEEE Transactions on Power Electronics, 2020, 35(8): 8361-8373. [18] Yang Ming, Lang Xiaoyu, Long Jiang, et al.Flux immunity robust predictive current control with incremental model and extended state observer for PMSM drive[J]. IEEE Transactions on Power Elec- tronics, 2017, 32(12): 9267-9279. [19] Wang Fengxiang, Ke Dongliang, Yu Xinhong, et al.Enhanced predictive model based deadbeat control for PMSM drives using exponential extended state observer[J]. IEEE Transactions on Industrial Elec- tronics, 2022, 69(3): 2357-2369. [20] Hu Mingjin, Hua Wei, Wang Zuo, et al.Selective periodic disturbance elimination using extended harmonic state observer for smooth speed control in PMSM drives[J]. IEEE Transactions on Power Electronics, 2022, 37(11): 13288-13298. [21] Hou Qiankang, Ding Shihong.Finite-time extended state observer-based super-twisting sliding mode controller for PMSM drives with inertia identi- fication[J]. IEEE Transactions on Transportation Electrification, 2022, 8(2): 1918-1929. [22] Zhang Yongchang, Jin Jialin, Huang Lanlan.Model- free predictive current control of PMSM drives based on extended state observer using ultralocal model[J]. IEEE Transactions on Industrial Electronics, 2021, 68(2): 993-1003.