基于改进粒子群算法的PID控制器参数整定优化

针对经典粒子群算法应用在PID控制器参数上整定的方法效果往往不佳的问题上，提出了一种改进粒子群算法的PID控制器参数整定优化设计，在粒子群的基础上加入遗传算法中的交叉算子，并将粒子群中的惯性权重因子改成动态参数，应用到PID控制器，使参数的自适应整定问题也获得了改进，快速性和稳定性也都优于经典粒子群算法的PID控制器．借助Matlab获得仿真系统的响应曲线图，根据对比得出系统性能的指标改进情况．

Optimization Design of PID Controller based on Particle Swarm Optimization Algorithm

In view of the classic particle swarm algorithm in PID controller parameter setting method of its effect is often poor, this paper puts forward an improved particle swarm algorithm optimization design of the PID controller parameter setting, on the basis of the particle swarm to join the crossover operator of genetic algorithm, and the particle swarm of inertia weight factor into a dynamic parameter, The applied PID controller improves the adaptive tuning of parameters, and the rapidity and stability are better than those of the classical PSO PID controller. With the help of Matlab to simulate the response curve of the system, according to the comparison of the system performance index improvement.