Fuzzy H∞ robust control for magnetic levitation system of maglev vehicles based on T-S fuzzy model: Design and experiments

• Published in: Journal of intelligent & fuzzy systems Vol. 36; no. 2; pp. 911 - 922
• Main Authors: Sun, You-Gang, Xu, Jun-Qi, Chen, Chen, Lin, Guo-Bin
• Format: Journal Article
• Language: English
• Published: Amsterdam IOS Press BV 2019
• Subjects: Computer simulation; Control stability; Control systems; Control theory; Controllers; Disturbances; Dynamic response; Economic models; Feedback control; Fuzzy control; Fuzzy systems; H-infinity control; Magnetic levitation; Magnetic levitation systems; Magnetic levitation vehicles; Mathematical analysis; Matrix methods; Performance indices; Proportional integral derivative; Robust control; Robustness (mathematics); Stability; State feedback; Uncertainty; Vehicles
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-169868

The magnetic levitation systems of maglev vehicles face the problems of open-loop instability, strong nonlinearity, model uncertainty, and large external disturbances. In order to solve the problems of model uncertainty and exogenous disturbances simultaneously, a T-S fuzzy model of magnetic levitation system with exogenous disturbances and model uncertainties is constructed to obtain an overall control model. A fuzzy H∞ robust state feedback controller for magnetic levitation systems is designed based on parallel distribution compensation (PDC) design method and the proposed T-S model. The quadratic stability of the closed-loop magnetic levitation system with fuzzy robust control law is proved. The linear matrix inequality (LMI) is utilized to obtain a controller which can satisfy the H∞ performance index and the stability of the magnetic levitation system with the proposed control law is proved by Lyapunov method. Both simulation and experimental results are included to demonstrate that the proposed control law can ensure the stable suspension of the vehicle and can restrain the exogenous disturbance effectively. Compared with conventional PID controller, the presented controller can assure faster dynamic response, stronger robustness and smaller overshoot under both exogenous disturbances and model uncertainties.