|
|
|
| Model-Free High Sliding Mode Control for Permanent Magnet Synchronous Motor |
| Zhao Kaihui1, Liu Wenchang1, Liu Zhicheng1, Jia Lin2, Huang Gang2 |
1. College of Electrical and Information Engineering Hunan University of Technology Zhuzhou 412007 China;
2. College of Railway Transportation Hunan University of Technology Zhuzhou 412007 China |
|
|
|
Abstract Permanent magnet synchronous traction systems have been widely used in high-speed trains and urban rail because of the advantages of high power density, high overload capacity, and fast dynamic torque. PI control technology has become the mainstream control method for motors owing to the advantages of the simple method and easy engineering implementation. However, PMSM is susceptible to unknown disturbances, parameter perturbation, and other uncertainties under complex traction conditions, and it is difficult to suppress the disturbances using traditional PI control. The overall control performance of the motor decreases, and satisfactory control results cannot be achieved in high-performance applications. The control performance of high torque permanent magnet traction synchronous motor in urban rail transit is degraded by uncertainties. Therefore, this paper proposes a novel model-free non-singular fast terminal sliding mode control strategy for the speed loop based on an extended non-singular terminal sliding mode disturbance observer.
Firstly, a novel ultra-model is established based on the mathematical model of the permanent magnet synchronous traction motor under parametric perturbation and unknown perturbations using the input and output of the speed loop. Secondly, the model-free non-singular fast terminal sliding mode controller is designed based on the novel ultra-model. Then, combined with the higher-order sliding and non-singular terminal sliding modes, a real-time observer is designed for estimating the unknown part of the novel ultra-model. Consequently, the system’s robustness is improved by the feedforward compensation of the controller, the control accuracy of the speed is improved, and the system jitter is reduced. Finally, a comprehensive comparison with PI control and model-free sliding mode control (MFSMC) by simulation and experiment is carried out. It is shown that the proposed control method has strong fault tolerance and anti-disturbance to motor perturbation and unknown disturbances. In addition, the dependence on the accurate mathematical model of the motor can be reduced.
Simulation and experimental results show that compared with the PT control and MFSMC method, the speed controlled by the MFNFTSMC method is the least affected by the change of rotational inertia. The speed controlled by the PI control and MFSMC method cannot recover to the given speed when the load torque changes and the resistance and inductance parameters are perturbation. In contrast, the speed controlled by the MFNFTSMC method can accurately track the given speed quickly. Meanwhile, the A-phase current total harmonics distortions (THD) of PI control and MFSMC method under parameter perturbation are 9.31 % and 7.35 %, while the MFNFTSMC method is reduced to 4.15 %. Thus, the MFNFTSMC method has an effective suppression of current harmonics. Similarly, compared with the PI control and MFSMC method, the proposed MFNFTSMC method achieves lower torque pulsation: the torque errors of the PI control and MFSMC method are about 16 % and 12.5 %, while the proposed MFNFTSMC method is only about 7.75 %. As a result, the MFNFTSMC method effectively suppresses the current pulsation problem under parameter perturbation.
The following conclusions can be drawn from the simulation and experimental analysis: (1) Combining the MFC method and NFTSM to design the model-free nonsingular fast terminal sliding mode controller, the speed, current, and torque of the motor are recovered to the given value in a short time under the parameter and unknown perturbations, and the dynamic response speed and robustness of the system are improved. (2) The designed ENTSMDO can accurately observe the unknown part of the ultra-local model in real-time and effectively suppress the current and torque ripple through the feedforward compensation of the controller, ensuring high-performance control of the motor. (3) Compared with PT control and the MFSMC method, the ENTSMDO-based MFNFTSMC method has better transient and steady-state performance and more robust anti-interference capability under motor parameter perturbation and external disturbance. It achieves fault- tolerant control of the motor under parameter perturbation.
|
|
Received: 18 April 2022
|
|
|
|
|
|
[1] 姚钢, 杨浩猛, 周荔丹, 等. 大容量海上风电机组发展现状及关键技术[J]. 电力系统自动化, 2021, 45(21): 33-47.
Yao Gang, Yang Haomeng, Zhou Lidan, et al.Deve- lopment status and key technologies of large-capacity offshore wind turbines[J]. Automation of Electric Power Systems, 2021, 45(21): 33-47.
[2] 刘寅迪, 曾翔君, 骆一萍, 等. 基于MPPMSG的混合高压直流风电系统故障穿越技术[J]. 电力系统自动化, 2020, 44(8): 133-140.
Liu Yindi, Zeng Xiangjun, Luo Yiping, et al.Fault ride-through technology of hybrid HVDC wind power system based on multi-phase permanent magnet synchronous generator[J]. Automation of Electric Power Systems, 2020, 44(8): 133-140.
[3] 高锋阳, 齐晓东, 李晓峰, 等. 部分分段Halbach永磁同步电机优化设计[J]. 电工技术学报, 2021, 36(4): 787-800.
Gao Fengyang, Qi Xiaodong, Li Xiaofeng, et al.Optimization design of partially-segmented Halbach permanent magnet synchronous motor[J]. Transa- ctions of China Electrotechnical Society, 2021, 36(4): 787-800.
[4] Zhao Kaihui, Zhou Ruirui, She Jinhua, et al.Demagnetization-fault reconstruction and tolerant- control for PMSM using improved SMO-based equivalent-input-disturbance approach[J]. IEEE/ASME Transactions on Mechatronics, 2022, 27(2): 701-712.
[5] 鲍旭聪, 王晓琳, 顾聪, 等. 超高速永磁电机驱动系统电流环稳定性分析与改进设计[J]. 电工技术学报, 2022, 37(10): 2469-2480.
Bao Xucong, Wang Xiaolin, Gu Cong, et al.Stability analysis and improvement design of current loop of ultra-high-speed permanent magnet motor drive system[J]. Transactions of China Electrotechnical Society, 2022, 37(10): 2469-2480.
[6] Niu Feng, Chen Xi, Huang Shaopo, et al.Model predictive current control with adaptive-adjusting timescales for PMSMs[J]. CES Transactions on Elec- trical Machines and Systems, 2021, 5(2): 108-117.
[7] 张晓光, 闫康, 张文涵. 开绕组永磁同步电机混合双矢量模型预测控制[J]. 电工技术学报, 2021, 36(1): 96-106.
Zhang Xiaoguang, Yan Kang, Zhang Wenhan.Hybrid double vector model predictive control for open- winding permanent magnet synchronous motor with common DC bus[J]. Transactions of China Elec- trotechnical Society, 2021, 36(1): 96-106.
[8] Shao Yanzhen, Yu Yanjun, Chai Feng, et al.A two-degree-of-freedom structure-based backstepping observer for DC error suppression in sensorless PMSM drives[J]. IEEE Transactions on Industrial Electronics, 2022, 69(11): 10846-10858.
[9] 肖飞, 许观达, 连传强, 等. 永磁同步电机单电流传感器系统的三相电流重构策略[J]. 电工技术学报, 2022, 37(7): 1609-1617.
Xiao Fei, Xu Guanda, Lian Chuanqiang, et al.Three- phase current reconstruction strategy of permanent magnet synchronous machine drives using a single current sensor[J]. Transactions of China Electro- technical Society, 2022, 37(7): 1609-1617.
[10] Guo Fei, Chu Qiu, Li Chunyan, et al.Research on influence of motor parameters on the negative-salient permanent magnet synchronous motor[J]. CES Transactions on Electrical Machines and Systems, 2022, 6(1): 77-86.
[11] 魏惠芳, 王丽梅. 永磁直线同步电机自适应模糊神经网络时变滑模控制[J]. 电工技术学报, 2022, 37(4): 861-869.
Wei Huifang, Wang Limei.Adaptive fuzzy neural network time-varying sliding mode control for per- manent magnet linear synchronous motor[J]. Transa- ctions of China Electrotechnical Society, 2022, 37(4): 861-869.
[12] Hou Qiankang, Ding Shihong, Yu Xinghuo.Com- posite super-twisting sliding mode control design for PMSM speed regulation problem based on a novel disturbance observer[J]. IEEE Transactions on Energy Conversion, 2021, 36(4): 2591-2599.
[13] Xu Wei, Junejo A K, Liu Yi, et al.An efficient antidisturbance sliding-mode speed control method for PMSM drive systems[J]. IEEE Transactions on Power Electronics, 2021, 36(6): 6879-6891.
[14] Yang Liang, Yang Jianying.Nonsingular fast terminal sliding-mode control for nonlinear dynamical systems[J]. International Journal of Robust and Nonlinear Control, 2011, 21(16): 1865-1879.
[15] 李升波, 李克强, 王建强, 等. 非奇异快速的终端滑模控制方法及其跟车控制应用[J]. 控制理论与应用, 2010, 27(5): 543-550.
Li Shengbo, Li Keqiang, Wang Jianqiang, et al.Nonsingular fast terminal-sliding-mode control method and its application on vehicular following system[J]. Control Theory & Applications, 2010, 27(5): 543-550.
[16] Liu Wei, Chen Siyi, Huang Huixian.Adaptive nonsingular fast terminal sliding mode control for permanent magnet synchronous motor based on dis- turbance observer[J]. IEEE Access, 2019, 7: 153791-153798.
[17] Xu Bo, Zhang Lei, Ji Wei.Improved non-singular fast terminal sliding mode control with disturbance observer for PMSM drives[J]. IEEE Transactions on Transportation Electrification, 2021, 7(4): 2753-2762.
[18] Zhao Kaihui, Liu Wenchang, Yin Tonghuan, et al.Model-free sliding mode control for PMSM drive system based on ultra-local model[J]. Energy Engin- eering, 2022, 119(2): 767-780.
[19] Fliess M, Join C.Model-free control[J]. International Journal of Control, 2013, 86(12): 2228-2252.
[20] Safaei A, Mahyuddin M N.Adaptive model-free control based on an ultra-local model with model-free parameter estimations for a generic SISO system[J]. IEEE Access, 2018, 6: 4266-4275.
[21] Zhao Kaihui, Yin Tonghuan, Zhang Changfan, et al.Robust model-free nonsingular terminal sliding mode control for PMSM demagnetization fault[J]. IEEE Access, 2019, 7: 15737-15748.
[22] 赵凯辉, 周瑞睿, 冷傲杰, 等. 一种永磁同步电机的有限集无模型容错预测控制算法[J]. 电工技术学报, 2021, 36(1): 27-38.
Zhao Kaihui, Zhou Ruirui, Leng Aojie, et al.Finite control set model-free fault-tolerant predictive control for permanent magnet synchronous motor[J]. Transa- ctions of China Electrotechnical Society, 2021, 36(1): 27-38.
[23] 赵凯辉, 殷童欢, 张昌凡, 等. 永磁同步电机无模型滑模控制方法研究[J]. 电子测量与仪器学报, 2018, 32(4): 172-180.
Zhao Kaihui, Yin Tonghuan, Zhang Changfan, et al.Research on model-free sliding mode control of permanent magnet synchronous motor[J]. Journal of Electronic Measurement and Instrumentation, 2018, 32(4): 172-180.
[24] Mousavi M S, Davari S A, Nekoukar V, et al.Integral sliding mode observer-based ultralocal model for finite-set model predictive current control of induction motor[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2022, 10(3): 2912-2922.
[25] 赵凯辉, 戴旺坷, 周瑞睿, 等. 基于扩展滑模扰动观测器的永磁同步电机新型无模型滑模控制[J]. 中国电机工程学报, 2022, 42(6): 2375-2386.
Zhao Kaihui, Dai Wangke, Zhou Ruirui, et al.Novel model-free sliding mode control of permanent magnet synchronous motor based on extended sliding mode disturbance observer[J]. Proceedings of the CSEE, 2022, 42(6): 2375-2386.
[26] Banerjee R, Sensarma P.Improved analytical method to determine flux-linkage characteristics of a switched reluctance machine[J]. IEEE Transactions on Industry Applications, 2020, 56(6): 6314-6323.
[27] 冯勇, 鲍晟, 余星火. 非奇异终端滑模控制系统的设计方法[J]. 控制与决策, 2002, 17(2): 194-198.
Feng Yong, Bao Sheng, Yu Xinghuo.Design method of non-singular terminal sliding mode control systems[J]. Control and Decision, 2002, 17(2): 194-198.
[28] Fallaha C J, Saad M, Kanaan H Y, et al.Sliding-mode robot control with exponential reaching law[J]. IEEE Transactions on Industrial Electronics, 2011, 58(2): 600-610.
[29] 李慧洁, 蔡远利. 基于双幂次趋近律的滑模控制方法[J]. 控制与决策, 2016, 31(3): 498-502.
Li Huijie, Cai Yuanli.Sliding mode control with double power reaching law[J]. Control and Decision, 2016, 31(3): 498-502.
[30] Lu En, Li Wei, Yang Xuefeng, et al.Anti-disturbance speed control of low-speed high-torque PMSM based on second-order non-singular terminal sliding mode load observer[J]. ISA Transactions, 2019, 88: 142-152.
[31] Khalil H K.Nonlinear systems[M]. 3rd ed. Upper Saddle River, NJ: Prentice Hall, 2002. |
|
|
|
2023, Vol. 38 
