Adaptive Fuzzy Super-twisting Sliding Mode Control for the Multi-electromagnets Levitation System of Maglev Vehicles: Design and Experiments

High-speed maglev vehicles offer significant advantages in environmental protection and climbing ability, positioning them as a key future transportation mode. However, maglev vehicles suffer from the coupling effect between multiple electromagnets, track irregularity, and time-varying disturbance (changes in aerodynamic lift and number of passengers carried, etc.), which bring challenges for system uncertainties in compensation and controller design. In addition, many current controllers, which rely on precise model knowledge, fail to guarantee satisfactory levitation, posing potential safety hazards in real-world applications. To address the above problems, this paper proposes an adaptive fuzzy compensation-based super-twisting sliding mode control (AFSTC) method designed to achieve precise levitation based on the original nonlinear dynamics of the levitation system without any linearization operation. Specifically, the proposed update law adaptively addresses the parameter and structural uncertainties of the levitation system. Leveraging the super-twisting sliding mode control law, the airgap can attain the desired target within a finite time, and system chattering can be significantly mitigated. The asymptotic stability of all state variables in the levitation system is rigorously validated through Lyapunov analysis. Simulation and experimental results underscore the effectiveness and robustness of the proposed AFSTC method.