基于改进粒子群算法的PID控制器参数优化

粒子群优化算法是一种性能优越的寻优算法,但由于早熟问题,影响了算法性能的发挥,同时PID控制器是一类广泛使用的控制器,其参数的选取可等效为优化问题,在标准微粒子群算法的基础上,分析了惯性权重对不同粒子的影响,提出了一种基于适应度值的多惯性权重动态调整机制,同时针对标准微粒子群算法易陷入局部最优的特点,引入混沌扰动机制,利用混沌的遍历性、随机性来改善种群的多样性,并将该方法用于PID控制器参数整定,仿真结果表明了方法的有效性和优越性。

Optimization of PID Controller Paramerters Based on Improved Particle Swarm Algorithms

Particle Swarm Optimizer is a probability algorithm with excellent performance.But the premature phenomenon limits the effect of PSO.PID controller is a widely used controller,its performance depends on the optimization of PID controller paramerters.Based on the standard PSO algorithm,the influence of inertial weight on different particles is analyzed,and a Multi-weight dynamic adjusting mechanism based on fitness value is proposed. In view the disadvantage that the standard PSO algorithms would easily be t...