多级思维进化寻优的模糊PID控制器设计

Design of a Fuzzy PID Controller Employed Multilevel Mind Evolution Algorithm

为了提高模糊PID控制器的适应性,首先对模糊PID控制器进行简化处理,简化后的PID被控参数与量化因子、比例因子和解析规则相结合,构成多参数寻优的模糊PID控制器,同时采用多级"思维进化算法"对参数进行分组分阶段交替寻优,以适应各种环境的变化。仿真结果表明,MEA-模糊PID控制系统的结构合理,解决了模糊控制中参数优化问题,取得了良好的控制效果;同时在保证控制效果的情况下,大大简化了模糊PID控制器的设计。

To improve the adaptabililty of fuzzy PID controller, this paper firstly simplifies fuzzy PID controller,then unifies the PID controlled parameters,measure gene,proportional gene and rules parsed,at last, mind evolution algorithm is used to optimize all these parameters by grouping.The simulation results have shown that the MEA-fuzzy PID control system has correct structure and improved control quality,which help finding optimal parameters.All these make it possible that design of fuzzy PID controller becomes very easy.