An Enhanced Tuning of PID Controller via Hybrid Stochastic Fractal Search Algorithm for Control of DC Motor

Abstract

AbstractThe fusion of Stochastic Fractal Search (SFS) and Pattern Search (PS) Technique Hybrid SFS (HSFS) has been applied to optimize the parameters of PID controller for controlling the celerity of DC motor with ITAE fitness/objective function. SFS algorithm is easy to implement and simple. It utilizes diffusion property present inside random fractals to find out search space. This approach has been combined with Pattern Search (PS) optimization which is derivative free good evolutionary algorithm for solving the complex problems. It utilizes balanced and adaptable operator to optimize local search excellently by enhancing global search. The simulation results of the proposed HSFS–PID controller optimized by the same have too been compared with recently published different techniques in the literature. The simulation results depict that the proposed HSFS-PID controller optimized by HSFS shows less ITAE value and far better performance in transient response like fast and smooth dynamic response with less oscillations when compared with other approaches in the literature for the same considered system and same fitness/objective function (ITAE).KeywordsHybrid Stochastic Fractal SearchPattern SearchDC Motor