张 铸,饶盛华,张小平,王静袁.基于FOA-RBF的管状开关磁阻直线电机直接瞬时出力控制[J].电子测量与仪器学报,2020,34(1):141-148
基于FOA-RBF的管状开关磁阻直线电机直接瞬时出力控制
Instantaneous force control of a linear switched reluctance actuator based on FOA-RBF
  
DOI:
中文关键词:  开关磁阻电机  果蝇算法优化径向基神经网络  直接瞬时出力控制  力分配函数
英文关键词:linear switched reluctance motor  FOA RBF  direct instantaneous force control  force distribution function
基金项目:国家自然科学基金(61503132)、长株潭国家自主创新示范区专项(2017XK2303)、湘潭市科技专项(CXY ZD20172001)资助
作者单位
张 铸 1.湖南科技大学信息与电气工程学院 
饶盛华 2.湖南科技大学海洋矿产资源探采装备与安全技术国家地方联合工程实验室 
张小平 2.湖南科技大学海洋矿产资源探采装备与安全技术国家地方联合工程实验室 
王静袁 1.湖南科技大学信息与电气工程学院 
AuthorInstitution
Zhang Zhu 1. College of Information and Electrical Engineering, Hunan University of Science and Technology 
Rao Shenghua 2.NationalLocal Joint Engineering Laboratory of Marine Mineral Resources Exploration Equipment and Safety Technology,Hunan University of Science and Technology 
Zhang Xiaoping 2.NationalLocal Joint Engineering Laboratory of Marine Mineral Resources Exploration Equipment and Safety Technology,Hunan University of Science and Technology 
Wang Jingyuan 1. College of Information and Electrical Engineering, Hunan University of Science and Technology 
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中文摘要:
      以车辆主动悬架系统为应用背景,针对径向磁通的管状开关磁阻直线电机提出了一种基于果蝇算法优化径向基神经网络模型(FOA-RBF)的直接瞬时出力控制方法。利用台架测量得到的电机出力样本对FOA-RBF进行离线训练,完成电流、动子位置到出力的非线性映射,构造出基于FOA-RBF的出力观测器对电机出力进行实时在线估算,并与出力分配函数相结合,实现相邻两相出力目标值的动态调整,有效地抑制了出力波动并降低了各相电流峰值。该控制方法利用了FOA-RBF神经网络泛化和逼近能力强的优点,出力计算速度快、精度高,满足实时控制要求。基于台架实际测量的电机出力和电磁特性,结合运动方程在MATLAB/Simulink环境中构建了系统仿真模型,并对提出的控制策略进行了仿真验证。最后搭建实验平台对电机动态性能进行了测试,进一步验证了FOA-RBF出力估算和控制算法的有效性。
英文摘要:
      A direct instantaneous force control scheme based on FOA-RBF was proposed for the tubular linear switched reluctance actuator with radial flux. The FOA-RBF was trained off line by the samples obtained from bench measurements, and nonlinear mapping from current and translator position to output force was completed. After training, FOA-RBF was applied for the real time estimation of output force, and dynamic adjustment of required force between adjacent phases was realized with the combination of force distribution function. The output force ripple and peak phase current were effectively restrained. The proposed control algorithm makes use of the advantages of generalization and approximation ability of FOA-RBF. Fast force estimation and high precision are achieved, which can meet the requirement of real time control. Based on the actual measurements of force and electromagnetic characteristics, the system simulation model was constructed and applied to verify the control method. Finally, the experimental platform was built, and the effectiveness of FOA-RBF and proposed control algorithm is further verified.
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