基于改进的萤火虫算法的PID控制器参数寻优

PID CONTROLLER PARAMETER OPTIMIZATION BASED ON IMPROVED GLOWWORM SWARM OPTIMIZATION

PID控制器的参数寻优是当代反馈控制系统设计的核心内容。PID控制器参数寻优意味着在三个参数空间域中寻找最优解,使得控制系统的性能达到最佳。为更好地对PID控制器的参数整定,引入自适应变步长策略的群智能萤火虫算法。利用MATLAB进行仿真实验,与粒子群(PSO)算法和经典的Z-N参数整定方法进行比较。实验表明,所提算法精度高、原理简单,可高效整定PID控制器参数。

PID controller parameter optimization is the core of contemporary feedback control system design. PID controller parameter optimization means that in the three parameter space domain to find the optimal solution, making the control system performance to achieve the best. In order to optimize the parameters of PID controller, the improved GSO with adaptive step size strategy is introduced. The algorithm is simulated by MATLAB, and compared with PSO and classical Z-N parameter tuning method. Experiments show that the algorithm has high precision and simple principle, and it can efficiently set the parameters of PID controller.