基于改进粒子群算法的PID控制参数优化

针对粒子群优化算法(particle swarm optimization algorithm,PSO)后期易陷入局部最优解这一缺陷,提出一种惯性权重余弦调整的粒子群优化算法(IWCPSO)。在迭代过程中对惯性权重引入余弦变化,改善迭代后期的不足,提高算法的精度。在matlab 2016仿真环境下,与Ziegler-Nichols(ZN)公式法和惯性权重正弦调整的粒子群优化算法(SIPSO)在PID控制参数优化方面的应用效果对比得出该算法是一种使得PID控制系统响应函数性能指标更好,整定结果更精确的算法。

Optimization of PID control parameters based on improved particle group algorithm

A particle swarm optimization algorithm(IWCPSO)with cosine adjustment of inertia weight was proposed to solve the problem that PSO is prone to fall into local optimal solution.In this algorithm,cosine change was introduced to the inertia weight during the iteration process,which obviously improved the deficiency in the later iteration and improved the accuracy of the algorithm.In the matlab 2016 simulation environment,Ziegler-Nichols(ZN)formula method and inertia weight sinusoidal adjustment particle swarm optimization algorithm(SIPSO)were compared in application effects of PID control parameter optimization,results show that the proposed algorithm makes the performance index of PID control system response function better,and makes the tuning results of the algorithm more precise.