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无刷直流电机(BLDCM)是一个多变量、非线性、强耦合、时变的系统。系统使用电流和转速双闭环控制,速度环采用自适应模糊PID控制器作为调速模块。针对模糊PID控制器在隶属函数和模糊控制规则存在的不足,提出利用改进的遗传算法优化模糊PID控制器。在遗传算法的基础上,针对该算法进行改进,将隶属度函数和模糊控制规则表统一编码,然后利用改进遗传算法对这一统一编码串进行全局寻优。Matlab/Simulink仿真结果表明优化后的系统响应时间更短、控制精度更高、鲁棒性更强,具有很好的应用推广价值。
Brushless DC Motor (BLDCM) is a multivariable, nonlinear, strongly coupled, time-varying system. The system uses the current and speed double closed-loop control, the speed loop adaptive fuzzy PID controller as the speed control module. Aiming at the deficiency of membership function and fuzzy control rules of fuzzy PID controller, this paper proposes an improved fuzzy genetic algorithm to optimize fuzzy PID controller. Based on the genetic algorithm, this algorithm is improved, and the membership function and the fuzzy control rules table are uniformly encoded. Then, the improved global genetic algorithm is used to optimize the global encoding sequence. The simulation results of Matlab / Simulink show that the optimized system response time is shorter, the control precision is higher and the robustness is stronger, so it has good application and popularization value.