基于SSA优化的永磁同步电机级联模型预测控制研究  

Predictive Control Study of Cascade Model for Permanent Magnet Synchronous Motors Based on SSA Optimization

作　　者：蔡宏越 马家庆 何志琴[1] 吴钦木[1] 陈昌盛[1] 覃涛[1] CAI Hongyue;MA Jiaqing;HE Zhiqin;WU Qinmu;CHEN Changsheng;QIN Tao(The Electrical Engineering College,Guizhou University,Guiyang 550025,China)

机构地区：[1]贵州大学电气工程学院,贵阳550025

出　　处：《组合机床与自动化加工技术》2024年第7期79-82,88,共5页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金资助项目(62163006);贵州省科技计划项目(黔科合支撑[2021]一般442,[2022]一般264,[2023]一般096,[2023]一般179)。

摘　　要：针对永磁同步电机(permanent magnet synchronous motor)使用传统PI控制鲁棒性差和动态响应慢,以及传统有限集电流预测控制方法控制稳定性差和电流脉动较大的问题,提出了基于麻雀搜索算法(sparrow search algorithm,SSA)优化的级联模型预测控制方法。首先,将速度外环采用模型预测速度控制器,利用麻雀搜索算法来在线整定控制器参数,该方法可以快速找到最优的控制器参数,使其更加准确地控制电机运转;其次,电流内环采用最优占空比模型预测电流控制器,使得电流脉动减小;最后,通过仿真对比实验结果表明所提出的控制方法显著地降低了超调量,快速响应性能更好、抗干扰能力更优,同时可以有效抑制电流脉动,证明了所提方法的合理性和有效性。Aiming at the problems that the poor robustness and slow dynamic response of the traditional PI control of permanent magnet synchronous motor,as well as poor control stability and large current pulsation of the traditional finite set current prediction control method,a cascade model predictive control method based on the optimization of the sparrow search algorithm is proposed.Firstly,the speed loop uses a model predictive speed controller,using a sparrow search algorithm to adjust the controller parameters online.This method allows the optimal controller parameters to be found quickly,making it possible to control the motor operation more accurately.Secondly,the current loop uses the optimal duty cycle model to predict the current controller,which reduces the current pulsation.Finally,simulation and comparison experimental results show that the proposed control method significantly reduces overshoot,has better fast response performance and better anti-interference capability,and can effectively suppress current pulsation,which proves the rationality and effectiveness of the proposed method.

关 键 词：永磁同步电机 麻雀搜索算法 模型预测控制 最优占空比 级联 

分 类 号：TH165[机械工程—机械制造及自动化] TG659[金属学及工艺—金属切削加工及机床]