T-S Fuzzy Control of Magnetic Levitation Systems Using QEA

This paper proposed the design of T-S fuzzy control for magnetic levitation systems. The maglev systems are linearized at the equilibrium point first. Then the error state equations are derived and the proportional integral (PI) controller is applied to eliminate the steady-state tracking error. The nonlinear dynamic equations of the magnetic levitation systems are represented by a T-S fuzzy model. The optimal gains are found by using particle swarm optimization (PSO) and quantum-inspired evolutionary algorithm (QEA) respectively. The stability of the system is guaranteed by linear matrix inequalities (LMI) from Lyapunov approach. Computer simulations demonstrate the effectiveness of this design.