PID Parameter Optimization Based On The Improved Moth Flame Optimization Algorithm

PID parameters are of great significance to the stability, reliability and rapid response of the system. To further improve the PID parameters, this paper selects the improved moth flame optimization (IMFO) to optimize the PID controller parameters of unstable systems. The Latin hypercube sampling and simplex method were selected to improve the moth to the flame algorithm. Through MATLAB simulation, the optimization results of the PID controller by the IMFO were compared with those of the moth flame optimization, the MFO algorithm with the Latin hypercube sampling initialization population, particle swarm algorithm, and salp swarm algorithm. The results show that the improved moth to flame algorithm can enhance the control accuracy and response speed of the system.