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<p>In this paper, a generalized multivariable adaptive super-twisting algorithm is proposed. Finite-time convergence is achieved for a family of Multivariable Super-Twisting functions, which ensures robustness for a broader class of disturbances. Furthermore, based on the Dual-Layer adaptive scheme, the adaptation gain is able to tune the gains of the algorithm while avoiding conservative choices, even when an upper-bound for the perturbation is unknown.</p>

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Generalized Multivariable Super-Twisting Algorithm Combined with an Adaptive Dual-Layer Scheme

  • 期刊论文

  • 发表日期：

    2025年5月5日

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  • Jair Luiz de Azevedo Filho,
  • Eduardo Vieira Leao Nunes

摘要

In this paper, a generalized multivariable adaptive super-twisting algorithm is proposed. Finite-time convergence is achieved for a family of Multivariable Super-Twisting functions, which ensures robustness for a broader class of disturbances. Furthermore, based on the Dual-Layer adaptive scheme, the adaptation gain is able to tune the gains of the algorithm while avoiding conservative choices, even when an upper-bound for the perturbation is unknown.