The suspension system in electromagnetic suspension maglev trains is highly nonlinear and sensitive to uncertainties, noise, and disturbances, making it quite challenging to design the proper electromagnetic voltages to control the suspension gap. In this paper, a self-tuning dual-layer sliding mode control system (SD-SMC) is developed to control the electromagnetic suspension system where voltage saturation, sensor noise, and a wide range of parametric uncertainties/variations exist. SD-SMC consists of dual-layer sliding mode controllers, a delay-compensated low-pass filter, and a forgetting least-squares estimator. Compared with existing control systems, SD-SMC can achieve high performance under large model uncertainties and disturbances with relatively low control voltages, and meanwhile, the control chattering and overshooting issues can be well mitigated. Both numerical and experimental examples are investigated to validate the proposed control system.


    Access

    Download


    Export, share and cite



    Title :

    Self-Tuning Dual-Layer Sliding Mode Control of Electromagnetic Suspension System


    Contributors:
    Li, Hong-Wei (author) / Zhang, Duo (author) / Lu, Yang (author) / Ni, Yi-Qing (author) / Xu, Zhao-Dong (author) / Zhu, Qi (author) / Wang, Su-Mei (author)


    Publication date :

    2025-02-01


    Size :

    2869927 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






    A dynamic sliding-mode controller with fuzzy adaptive tuning for an active suspension system

    Zhang, Yun-Qing / Zhao, Yong-Sheng / Yang, Jingzhou et al. | SAGE Publications | 2007


    A dynamic sliding-mode controller with fuzzy adaptive tuning for an active suspension system

    Zhang, Yun-Qing / Zhao, Yong-Sheng / Yang, Jingzhou et al. | Tema Archive | 2007


    A dynamic sliding-mode controller with fuzzy adaptive tuning for an active suspension system

    Zhang,Y.Q. / Zhao,Y.S. / Yang,J. et al. | Automotive engineering | 2007