改进遗传优化的无刷直流电机模糊PID控制

Fuzzy PID Control of Brushless DC Motor Based on Improved Genetic Algorithm

在无刷直流电机控制过程中,将智能控制与PID控制相结合生成智能PID控制策略,现有控制策略或者要求对被控过程有全面的先验知识,或者要求参数优化的搜索空间连续可微,其应用受到了一定的限制,提出基于改进遗传优化算法的无刷直流电机模糊PID控制方法。详细阐述了遗传算法的相关原理,在遗传算法的基础上,针对该算法进行改进,将无刷直流电机控制对象进行编码,构建对应的适应性函数,针对适应性函数进行定标,阐述改进遗传优化算法的终止条件,完成无刷直流电机模糊PID控制。实验结果表明,利用改进算法进行无刷直流电机模糊PID控制,能够缩短阶跃响应时间,降低控制误差,缩短控制过程中的延迟时间,满足无刷直流电机控制在生产过程中的实际需求。

in the process of brushless dc motor control, combining intelligent control with the PID control to gen- erate intelligent PID control strategy, the control strategy or require full process of charged with prior knowledge, or for parameter optimization search space continuously differentiable and its application is limited by a certain, reduce the accuracy of the brushless dc motor control. Therefore, based on improved genetic optimization algorithm of fuzzy PID control method for brushless dc motor. Of relevant principle of genetic algorithm （ga） is expounded in detail, on the basis of genetic algorithm, according to the algorithm was improved, the brushless dc motor control object coding and build the corresponding fitness function, fitness function for calibration, the termination conditions of improved genetic optimization algorithm, fuzzy PID control of BLDC motor. Experimental results show that the improved fuzzy PID control algorithm for brushless dc motor, can shorten the step response time, reduce the control error, shorten the delay time in the process of control, meet the brushless dc motor control in the actual demand in the process of production.