A Fuzzy-Logic-System-Based Cooperative Control for the Multielectromagnets Suspension System of Maglev Trains With Experimental Verification

Abstract

A maglev train is a sustainable public transport method with the characteristics of being green, pollution-free, and low-noise, as well as providing environmental protection. However, the performance of existing maglev control strategies for maglev trains may be deteriorated by various challenges, including disregard of the coordination and synchronization between multiple electromagnets, control input unidirectionality, dead zones, saturation, and finite time stability ability, etc. In this paper, an adaptive fuzzy-based suspension control method based on a multi-electromagnets dynamic coupling model is proposed that can cope with dead zone and saturation problems and guarantee the finite-time of the airgap tracking errors of multiple electromagnets simultaneously. Specifically, a fuzzy-logic system (FLS) is utilized to compensate for the nonlinear input unidirectionality, dead zone, saturation and unmodeled dynamics. Moreover, considering the coupling dynamic characteristics of adjacent electromagnet control modules, a fuzzy-based cooperative suspension controller with adaptive update law is designed. The finite time stability of the presented control strategy is proven with the Lyapunov method. Finally, the suspension frame experimental results are illustrated to validate the effectiveness and robustness of the developed method, whose superior performance is shown by being experimentally compared with some baseline methods.