In multimotor driving systems, inertia is one of the key parameters, and its variations can severely affect the control performance. This article proposes a novel adaptive discrete-time variable-power super-twisting control (ADVSC) to address this issue. To cater to practical digital control systems, a characteristic model is built in a discrete-time domain with fewer parameters and lower order, which decreases the complicacy of common dynamics models. The model parameters are acquired through online identification utilizing input and output data, which diminishes uncertainties and unknown dynamics. The ADVSC is then designed based on the characteristic model to meet practical performance requirements. Specifically, a variable-power sliding function is constructed to suit different tracking error intervals and accelerate the convergence process, and the super-twisting algorithm (STA) is further utilized to enhance robustness and meanwhile alleviate chattering. One attractive advantage of this strategy lies in that inertia variations can be reflected by time-varying parameters in the characteristic model using online identification, which endows the designed ADVSC with good adaptability. The stability of the closed-loop system is proved via the Lyapunov theory. Experiments are carried out on a multimotor servo control platform with adjustable load, and the obtained results validate the efficacy and practicality of the proposed strategy.


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    Title :

    Characteristic Model-Based Discrete-Time Adaptive Tracking Control for Multimotor Driving Systems With Inertia Variations


    Contributors:
    Wang, Xiang (author) / Wang, Baofang (author) / Chen, Xinkai (author) / Yu, Jinpeng (author)


    Publication date :

    2025-02-01


    Size :

    2287315 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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