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作 者:朱俊 王月武 朱艳[1] ZHU Jun;WANG Yuewu;ZHU Yan(School of Automation,Guangxi University of Science and Technology,Liuzhou 545616,China)
机构地区:[1]广西科技大学自动化学院,广西柳州545616
出 处:《广西科技大学学报》2024年第3期73-82,共10页Journal of Guangxi University of Science and Technology
基 金:广西高校中青年教师科研基础能力提升项目(2022KY0331);广西科技基地和人才专项(桂科AD23026152);广西科技大学博士基金项目(校科博21Z19)资助。
摘 要:永磁同步电机(permanent magnet synchronous motor,PMSM)单矢量模型预测电流控制(model predictive current control,MPCC)中,存在电流具有较大波动、稳态性能较差、依赖模型参数且抗扰能力不足的问题。针对这些问题,研究了双矢量模型预测电流控制(TV-MPCC)算法,该算法在一个采样周期内进行2次电压矢量选择。同时,设计了一种基于改进趋近率(SMRL)的滑模扰动观测器(SMO),滑模增益采用分段式函数来实现。通过仿真实验,验证了所提出的TV-MPCC算法和SMO的有效性。与传统的MPCC相比,TV-MPCC可以显著降低电流的波动,并提高系统的鲁棒性。同时,SMO的引入使得系统能够更好地观测和补偿扰动,进一步提高了系统的稳态性能。本研究表明,双矢量模型预测电流控制结合滑模扰动观测器的方法在提高PMSM的鲁棒性能方面具有较好的效果。In the context of single-vector model predictive current control for permanent magnet synchronous motors,there exist the problems such as significant current fluctuations,poor steady-state performance,dependence on model parameters,and insufficient disturbance rejection capability.To address these problems,a dual-vector model predictive current control algorithm was proposed,which performed two voltage vector selections within one sampling period.Additionally,an improved sliding mode observer based on modified reaching law was designed,where the sliding mode gain adopted a segmented function.The simulation experiments verified the effectiveness of the proposed TV-MPCC algorithm and SMO.Compared with the traditional MPCC,TV-MPCC significantly reduces current fluctuations and improves system robustness.Meanwhile,the introduction of SMO makes better observation and compensation of disturbances,enhancing the steady-state performance of the system.This study demonstrates that combining dual-vector model predictive current control with a sliding mode disturbance observer is effective in improving the robust performance of PMSM.
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