基于遗传算法的直流无刷电机控制

遗传算法是以自然选择与遗传理论为基础,将生物进化过程中适者生存原则与群体内部染色体的随机信息交换机制相结合的高效全局寻优搜索算法。本文以直流无刷电机为控制对象,对电机的转速系统进行优化设计,并对此结果进行Matlab的仿真。仿真结果显示随着迭代次数的递增,搜索结果参数对电机控制效果越来越优越,随着迭代次数的结束,算法寻找出最佳的控制参数。该算法全局寻优,对控制系统的参数优化明显,适用于复杂、非线性的直流无刷电机控制。

The Use of Genetic Algorithm on the Control of Brushless Direct Current Motor

Genetic algorithm(GA) is an efficient global optimization search algorithm that is based on natural selection and genetic theory and combines the principle of the survival of the fittest in the course of biological evolution with random information exchange mechanism of chromosomes within groups.In this paper,we use brushless DC motor(BLDCM) as the control object,optimize the design of the speed of the motor system and present the results of Matlab simulation.Simulation results show that with the increasing number of iterations,the search result parameters produce an increasingly superior effect on motor control,and with the end of iterations,the algorithm could find out the optimal control parameters.With its clear advantage of global optimization and parameter optimization of the control system,the algorithm could be applied to complex,nonlinear control of brushless DC motor(BLDCM).