Trajectory Tracking and Ball Position Control of Magnetic Levitation System using Swarm Intelligence Technique

Abstract

Magnetic levitation system is a second-order nonlinear system. The objective of the system is to levitate a metallic ball at a determined height under the influence of magnetic force by the principle of non-contact. In this paper, particle swarm optimization (PSO) technique is used to develop a controller to regulate the nonlinear dynamics in the magnetic levitation system. The proposed technique acts in parallel with a proportional integral derivative (PID) controller to balance the position of levitating ball in the air. Here, the optimization technique tunes the gain values of the PID controller for achieving better performance measures when applied to a nonlinear system. This tuning process adheres to search the optimal solution with the help of agents called as particles whose trajectories are adjusted by a deterministic component. Each particle is optimized by its best-achieved position through the iterative approach. Further, the performance of the proposed controller is demonstrated through simulation as well as on hardware. Both PID and PSO tuned PID controllers were designed and the dynamics of magnetic levitation system were tested. The results validate the performance of both conventional PID controller as well as PSO tuned PID controller enhancing the operation of the magnetic levitation system. It is observed that the PSO tuned PID overcomes the drawback of conventional PID by optimizing the performance parameters such as steady-state error and settling time.