电工技术学报  2023, Vol. 38 Issue (4): 903-914    DOI: 10.19595/j.cnki.1000-6753.tces.220074
电机及其系统 |
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
郭磊磊, 王朋帅, 李琰琰, 武洁, 王明杰
郑州轻工业大学电气信息工程学院 郑州 450002
Visual Analysis of Parameters Mismatch in Model Predictive Control for Permanent Magnet Synchronous Motor Under Different Cost Functions
Guo Leilei, Wang Pengshuai, Li Yanyan, Wu Jie, Wang Mingjie
College of Electrical and Information Engineering Zhengzhou University of Light Industry Zhengzhou 450002 China
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摘要 针对电机模型参数失配进行分析,该文提出一种可视化分析方法,分别研究了电阻、电感和磁链等参数失配对模型预测控制的影响。首先,结合无差拍控制原理计算得到满足控制要求的参考电压矢量;其次,分析电阻、电感和磁链等参数失配时参考电压矢量空间位置的变化,并利用Matlab算法对参数失配下参考电压矢量相应的最优电压矢量进行可视化表达;最后,通过最优电压矢量区域的不同变化得到不同参数失配对模型预测控制的影响。所提可视化分析方法不仅可以分析多种模型参数失配对控制系统的复杂影响,而且可以得到参数失配对不同代价函数下永磁同步电机模型预测控制最优电压矢量选择的影响和区别,为实现模型预测误差补偿控制提供坚实的理论依据。StarSim硬件在环实验研究验证了所提方法的可行性和有效性。
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郭磊磊
王朋帅
李琰琰
武洁
王明杰
关键词 永磁同步电机模型预测控制参数失配可视化分析代价函数    
Abstract:As the model predictive control (MPC) is conceptually clear and simple to implement with the ability to control several nonlinear objectives simultaneously, it is the preferred control method for permanent magnet synchronous motors (PMSM). However, the resistance, inductance, and other parameters in the current prediction model are vulnerable to nonlinear factors and changes in the load, resulting in model parameters mismatch, ultimately weakening the robustness and dynamic response ability of the MPC. Recently, although many papers have analyzed the influence of inductance and resistance mismatch on control performance, the influence of flux mismatch has yet to be considered. Additionally, the Euclidean norm, Euclidean norm square, and modular sum cost functions commonly used in MPC systems are considered equivalent. However, more theoretical analysis and experimental verification of the difference and relationship between the three cost functions are still necessary. Therefore, a visual analysis method is proposed to study the effects of different parameter mismatches on the MPC system of PMSM under different cost functions.
Firstly, the reference voltage that meets the control requirements is calculated based on deadbeat control principle. Secondly, the influence of parameters such as resistance, inductance, and flux linkage on the reference voltage is analyzed. The change of the reference voltage spatial position due to different parameter mismatches is determined. Then, based on the mismatched reference voltage, the optimal voltage vectors of different cost functions are obtained. Finally, the Matlab algorithm is used to visually express the selected optimal voltage vectors under all reference voltages. The influence and difference of parameter mismatch on the selection of optimal voltage vectors under different cost functions are analyzed by visualization method, which provides a solid theoretical basis for error compensation control methods.
The experiments of inductance and flux mismatch in the speed loop show that when the load torque is set to 10N·m, and the reference speed is stepped up from 150 r/min to 1 000 r/min, the inductance mismatch has an impact on the selection times of zero vector. Thus, the effective value of the total current error is greater than when the inductance is matched. Meanwhile, at low speed, the current ripples when the flux linkage is mismatched are similar to when the one is matched. However, at high speed, the current ripples and effective value of the total current error when the flux linkage is mismatched are significantly larger than when the one is matched. When the speed is set to 1 000 r/min and the load torque is changed from no-load to full load (25 N·m) and then to no-load, the current ripples and total current error when the inductance and flux linkage are mismatched are larger than those when the parameters are matched. Additionally, under the same conditions, the current ripples and the effective values of total current error under the two Euclidean norm cost functions are smaller than those under the modular sum cost function, indicating that the Euclidean norm cost functions have better control effects. The experimental results are consistent with the visualization analysis results, which shows the correctness and effectiveness of the proposed visualization method.
The following conclusions can be drawn from the theoretical and experimental analysis: (1) Parameter mismatches will affect the optimal voltage vector selection for the MPC method. (2) The MPC methods based on different cost functions have different parameter sensitivities. (3) The two Euclidean norm cost functions are preferred for MPC as they have smaller control errors when the parameters are mismatched.
Key wordsPermanent magnet synchronous motor    model predictive control    parameters mismatch    visual analysis    cost functions   
收稿日期: 2022-01-16     
PACS: TM341  
基金资助:河南省青年人才托举工程项目(2019HYTP021)和河南省科技攻关计划项目(212102210021)资助
通讯作者: 郭磊磊 男,1987年生,博士,副教授,主要研究方向为逆变器及交流电机的模型预测控制等。E-mail: 2006guoleilei@163.com   
作者简介: 王朋帅 男,1994年生,硕士研究生,主要研究方向为电力电子及电力传动。E-mail: 1019866626@qq.com
引用本文:   
郭磊磊, 王朋帅, 李琰琰, 武洁, 王明杰. 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, Wu Jie, Wang Mingjie. Visual Analysis of Parameters Mismatch in Model Predictive Control for Permanent Magnet Synchronous Motor Under Different Cost Functions. Transactions of China Electrotechnical Society, 2023, 38(4): 903-914.
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