基于自适应遗传算法的PID参数优化仿真研究

针对现有PID调节器的整定方法和遗传算法优化参数存在的问题，提出了一种自适应遗传算法用于PID参数寻优的方案。该算法采用了变群体规模和自动改变交叉概率、变异概率的措施，能提高算法的执行效率，收敛性较好，而且不易陷入局部最优解。以过热汽温控制系统为例，分别采用了简单遗传算法和改进遗传算法，对串级控制系统的PID参数寻优，仿真结果表明改进后的遗传算法具有较强的执行效率和很好寻优效果。

Simulating Study on PID Parameter Optimization Based on Adaptive Genetic Algorithm

Aiming at the existing problems of current PID tuning methods and simpl e genetic algorithm,an adaptive genetic one is brought out to optimize PID param eters.The algorithm,adopting variable population size and adaptive crossover,mu tation probability, can better improve the execution efficiency,convergence and be difficult to fall into local optimization.Taking an example of optimizing PID parameters of cascade control system,the simulation results show that,comparing with simple genetic algorithm ,improved genetic algorithm have higer efficiency and perfect optimization effect. What's more, the algorithm and strategy is a a ll-purpose method and can be applied to many other optimization problems.