Evolutionary computation based optimization of controller parameters for an Electromagnetic Levitation System

In this paper the optimized parameters of Lag-Lead and Proportional Integral Derivative (PID) controller for two-actuator based electromagnetic levitation system (EMLS) are determined using Evolutionary computation algorithms such as Particle Swarm Optimization (PSO) and a novel Gravitational Search algorithm (GSA). A comparative position response of EMLS (Electro Magnetic Levitation System) with classical, GSA and PSO based nominal controllers while operating at nominal and off-nominal (low and high) air-gaps have been studied. It is seen that GSA based optimized nominal PID controller shows excellent performance (both in transient and steady-state) over a large operating air-gap. The experimental results with the classical controller are also presented.