摘要
模糊控制在无刷直流电机(BLDCM)控制中应用广泛,针对其不能实时更新控制参数的缺点,首次提出了基于飞蛾火焰优化(MFO)算法的模糊控制器设计。对于BLDCM控制系统变量复杂且非线性,难以建立具体的数学模型的问题,搭建了电流和转速双闭环控制的模块化电机仿真模型。算法在线优化量化因子和比例因子,用ITAE验证适应度目标函数的合理性。仿真结果表明所提出的方法使得控制系统具有超调小和控制精度高的优点。
Fuzzy control was widely used in brushless DC motor(BLDCM)control.In view of its shortcoming that the control parameters couldn t be updated in real time,the design of fuzzy controller based on moth flame optimization(MFO)algorithm was proposed for the first time.For the problem that the variables of BLDCM control system were complex and nonlinear,it was difficult to establish specific mathematical model.A modular motor simulation model of double closed-loop control of current and speed was built.The algorithm optimized the quantization factor and scale factor online,and used ITAE to verify the rationality of the fitness objective function.Simulation results show that the proposed method makes the control system has the advantages of small overshoot and high control accuracy.
作者
刘雨豪
廖平
LIU Yu-hao;LIAO Ping(College of Mechanical and Electrical Engineering,Central South University,Changsha 410083,China)
出处
《仪表技术与传感器》
CSCD
北大核心
2021年第4期107-111,共5页
Instrument Technique and Sensor
基金
国家重点研发计划资助项目(2018AAA0101703)。
