基于免疫遗传算法的永磁无刷直流电机模糊控制.pdfVIP

基于免疫遗传算法的永磁无刷直流电机模糊控制 夏长亮 李 欣 (天津大学电气与自动化工程学院 天津市 300072) 摘要 利用免疫遗传算法 (immune genetic algorithm, IGA)对永磁无刷直流电机(brushless DC motor, BLDCM)模糊控制系统进行了参数优化。永磁无刷直流电机是一种多变量、非线性的控制 对象，传统控制理论难以获得满意的控制效果。模糊控制器虽然控制效果较好，但参数整定较为 困难，通常采用遗传算法(genetic algorithm, GA)等智能算法对其进行参数优化。针对利用遗传算 法优化模糊控制器存在的收敛速度较慢、参数难以同步优化、易陷入局部最优解等问题，引入免 疫遗传算法对永磁无刷直流电机双闭环调速系统中的模糊控制器进行参数同步优化，以时间误差 积分指标(integrated time and absolute error, ITAE)评价系统性能，并对编码方式进行改进。仿真和 实验结果表明，该方法收敛速度快，优化后的永磁无刷直流电机模糊控制系统响应速度快，速度 控制精度高，稳定性和鲁棒性强。 关键词：永磁无刷直流电机 免疫遗传算法 模糊控制 编码方式 时间误差积分指标 Control of Permanent Magnet Brushless DC Motor Using Immune Genetic Algorithm Based Fuzzy Logic Controller Xia Changliang Li Xin (School of Electrical Engineering and Automation, Tianjin University, Tianjin, 300072, China) Abstract This paper researches the optimization of immune genetic algorithm (IGA) in the fuzzy logic controller of permanent magnet brushless DC motor (BLDCM) system. As BLDCM is a multi-variable and non-linear system, conventional controllers can not obtain satisfied control effect. Fuzzy logic controller can improve the performance of BLDCM system, but it is difficult to design and set parameters. Genetic algorithm (GA) and other intelligent algorithms are usually solutions. In order to solve these problems of fuzzy logic controller based on GA as slow convergence, hard to simultaneously optimize parameters and tend to trap in local optimum, a fuzzy logic controller based on IGA is presented, which is applied into the BLDCM control system. Integrated time and absolute error (ITAE) is used as the term of fitness function. The simulation and experiment results show excellent flexibility and adaptability as