基于自适应遗传算法的协调控制系统优化

Optimization of a Coordinated Control System Based on the Self-adaptive Genetic Algorithm

针对火电单元机组的协调控制系统,提出了一种基于自适应遗传算法的多变量鲁棒PID控制器参数寻优方法。以控制器设定点跟踪性能为优化目标,鲁棒性能为动态约束,采用具有自适应交叉概率和变异概率的遗传算法寻优PID控制器参数。仿真结果表明,与传统遗传算法寻优所得PID控制器相比,基于自适应遗传算法的鲁棒PID控制器具有良好的负荷跟随性和更优的鲁棒性。

For coordinated control systems for elementary units in thermal power plants,presented was a searching method for optimizing the parameters of a multi-variable robust PID（proportional,integral and differential） controller based on the self-adaptive genetic algorithm.With the tracking performance of the controller at the set point serving as the optimization target and the robust performance as a dynamic constraint,the genetic algorithm involving a self-adaptive crossover and variation probability was employed to search optimal parameters of the PID controller.The simulation results show that compared with the PID controller optimized by using the traditional genetic algorithm,the robust PID one based on the self-adaptive genetic algorithm enjoys better load follow-up characteristics and a superior robustness.