Design of optimal controller for magnetic levitation system using Brownian bat algorithm

Abstract

This paper presents a method to design the One Degree Of Freedom(1DOF) and Two Degrees Of Freedom (2DOF) PID controllers for an unstable Magnetic Levitation System (MLS) using Brownian Bat Algorithm (BBA). Minimization of objective function (Jmin) is considered to guide the search towards the optimal controller parameters. A simulation study is carried to validate the performance of the proposed BBA with other successful heuristic algorithms, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bacterial Foraging Optimization (BFO) and Firefly Algorithm (FA). This study confirms that the proposed method offers better result in reference tracking operation with reduced error for 1DOF and 2DOF PID structure compared with other algorithms considered in this work.