PID Controller Optimization for Magnetic Ball Suspension System utilizing Genetic Algorithm

In this paper, The Magnetic Ball Suspension System (MBSS) has several real-world uses, including frictionless bearings, levitated wind tunnels, and high-speed trains. This is because of its intrinsic nonlinearities and extreme instability. As such, it’s a perfect platform for control system analysis and testing. The purpose of this work is to construct a PID controller specifically for the MBSS by utilizing an effective Genetic Algorithm (GA) based parameter tuning approach and lowering the integrals of absolute error, squared error, and time absolute error. The controller settings were adjusted using GA in order to maximize performance indices. An investigation was carried out to compare the performance of the GA-tuned PID controller with the conventionally tuned PID controller without implementing genetic algorithm. The GA-tuned PID controller outperformed its conventionally tuned equivalent, according to simulation data, validating the efficacy of the proposed approach.