Backstepping Control of a Magnetic Levitation System Using PSO

Magnetic levitation systems are highly nonlinear and unstable systems and their efficacy depends on a well-designed controller for stabilizing the system and for tracking the desired reference signal. This work focuses on the design of a backstepping controller for a magnetic levitation (maglev) system under parameter uncertainty which is load variation. The mathematical model is obtained and the stable controller is designed based on this model and Lyapunov's theorem. Then, the controller parameters are optimally tuned by minimizing the integral of absolute error and control deviation performance criterion using the particle swarm optimization (PSO) algorithm. For comparison purposes, a Proportional-Integral (PI) -type linear quadratic regulator is also designed. A set of simulation works are carried out in order to verify both the tracking performance and the robustness against disturbance for the proposed controller.