基于自适应遗传算法的PID参数寻优

PID parameter optimization based on adaptive genetic algorithm

针对工业过程中常见的二阶大滞后对象的PID参数调节问题,采用自适应遗传算法对PID控制进行参数寻优,并将结果与常用的PID参数寻优方法进行比较,仿真实验结果表明,在PID参数的寻优问题中,自适应遗传算法采用自动改变变异概率的方法,提高了控制系统的自适应性。

Aimed at PID parameter adjustment of second-order system models with long time-delay, which is common in industry process,adaptive generic algorithm（AGA） was adopted to optimize parameter on PID control, whose result was compared with the method of common PID parameter optimization. Simulation experiment result shows that AGA adopts the method of automatic change of mutation probability, which improves the self-adaptation, in the optimizing problem of PID parameter.