PID Parameter Tuning Based On Improved Cat Swarm Optimization And Its Application In DC Motor Control

With the complex characteristics of non-linearity,time lag and multi-dimension present in the actual production,the traditional PID parameter tuning method can no longer meet the many complex characteristics of the control system.With the development of swarm intelligence algorithms,the good global search capability of swarm intelligence algorithms can improve the accuracy of PID parameters,shorten the parameter setting time,and improve the performance of PID controllers.This paper proposes a PID parameter tuning method based on an improved cat swarm optimization and applies it to a DC motor control system.The main work includes the following aspects:1.In view of the shortcomings of the standard cat swarm optimization,the following improvements are proposed in the chaos quantum cat swarm optimization:(1)Improve the individual copy formula in the tracking mode so that the number of individual copies is proportional to the adaptation value,and enhance the algorithm's local search ability,Improve the accuracy of the local optimal solution of the algorithm;(2)Improve the allocation formula of the tracking mode and the search mode,through the dynamic value of the mixing rate,adapt to the changing needs of the number of cat groups in the two modes during the operation of the algorithm,and balance the locality of the algorithm Search and global search capabilities.In order to test the feasibility of improving the cat swarm optimization,five classic test functions were used to test the standard cat swarm optimization,chaos quantum cat swarm optimization and improved cat swarm optimization.The experimental results verified the feasibility and stability of the improved cat swarm optimization.2.A method for optimizing PID parameter tuning based on the improved cat swarm optimization is proposed,and the particle swarm optimization tuning method is used in four different typical controlled models(first order delay model,second order delay model,third order delay model and The fourth-order linear model)is compared with simulation experiments.The experimental results show that the control effect of the control system using this algorithm is better than the particle swarm optimization.3.Combined with the mathematical model of the DC motor,establish a simulation model of the DC motor control system,use the improved cat swarm optimization to optimize the PID parameters in the DC motor control system,and compare with the particle swarm optimization.The simulation results prove that the improved cat swarm optimization is based on Optimize the practicability of PID parameter setting.