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基于自适应扰动观测器的PMSM模型预测电流控制

Predictive Current Control of PMSM Model Based on Adaptive Disturbance Observer
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摘要 目的为了实现包装自动化生产线的高性能控制,针对永磁同步包装驱动电机在模型预测电流控制中对扰动敏感性较大的问题,设计一种基于自适应扰动观测器的模型预测电流控制策略。方法利用预测误差设计一种自适应扰动观测器,对系统遭受的内部和外部的不确定扰动,扰动观测器估计总扰动并以电流的形式进行补偿。将系统的瞬态过程和稳态过程分别进行考虑,设计一种含有动态权重因子的新型损失函数。结果通过MATLAB/SIMULINK仿真表明,与传统的控制方法相比,文中方法可以保持瞬态下的高速动态响应和稳态下的低电流纹波,并在应对参数失配和负载突变等问题上,展现了更好的稳态性能和抗干扰能力。结论文中方法可以有效提升系统动态性能和鲁棒性,使改进后系统更加适用于包装机的应用场景。 The work aims to design a predictive current control strategy of model based on adaptive disturbance observer,in order to realize the high-performance control of the packaging automation production line and solve the problem that the permanent magnet synchronous packaging drive motor is more sensitive to disturbance in the predictive current control of model.Firstly,an adaptive disturbance observer was designed by the prediction error.For the internal and external uncertain disturbances suffered by the system,the disturbance observer estimated the total disturbance and made compensation in the form of current.Moreover,the transient process and steady-state process of the system were considered separately,and a new loss function with dynamic weight factors was designed.The MATLAB/SIMULINK simulation showed that,compared with the traditional control method,the method proposed could maintain high-speed dynamic response in transient state and low current ripple in steady state,and show excellent performance in coping with parameter mismatch and load mutation.It has better steady-state performance and anti-interference ability.The method proposed can effectively improve the dynamic performance and robustness of the system,making the improved system more suitable for the application scenarios of packaging machines.
作者 金爱娟 张劲松 李少龙 JIN Ai-juan;ZHANG Jin-song;LI Shao-long(University of Shanghai for Science and Technology,Shanghai 200093,China)
机构地区 上海理工大学
出处 《包装工程》 CAS 北大核心 2023年第23期171-180,共10页 Packaging Engineering
基金 国家自然科学基金(11502145)。
关键词 永磁同步电机 自适应方法 扰动观测器 动态权重因子 permanent magnet synchronous motor adaptive method disturbance observer dynamic weighting factor
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