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<p>This study investigates the stabilization challenge at the boundaries of a type II thermoelastic network with <i>n</i>-star configuration and terminal masses, which experiences non-uniform bounded external disturbances at its control boundary. This research employs an advanced active disturbance rejection control framework, incorporating an innovative observer with adaptive gain characteristics for precise disturbance estimation, coupled with a robust feedback control mechanism for disturbance compensation. The theoretical analysis establishes rigorous convergence proofs for the proposed time-dependent extended state observer. Furthermore, this investigation utilizes semigroup theory to validate the closed-loop system’s well-posed. Through comprehensive Lyapunov-based analysis, this study confirms the system’s capability to achieve exponential convergence of tracking errors while effectively mitigating disturbance effects. Extensive numerical experiments corroborate the theoretical findings, demonstrating the control scheme’s practical efficacy.</p>

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Exponential stabilization of an n-star thermoelastic network system based on time-varying gains extended state observer

  • 期刊论文

  • 发表日期：

    2025年8月1日

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  • Lingwei Zheng,
  • Lei Wang,
  • Zhiqiang Gao

摘要

This study investigates the stabilization challenge at the boundaries of a type II thermoelastic network with n-star configuration and terminal masses, which experiences non-uniform bounded external disturbances at its control boundary. This research employs an advanced active disturbance rejection control framework, incorporating an innovative observer with adaptive gain characteristics for precise disturbance estimation, coupled with a robust feedback control mechanism for disturbance compensation. The theoretical analysis establishes rigorous convergence proofs for the proposed time-dependent extended state observer. Furthermore, this investigation utilizes semigroup theory to validate the closed-loop system’s well-posed. Through comprehensive Lyapunov-based analysis, this study confirms the system’s capability to achieve exponential convergence of tracking errors while effectively mitigating disturbance effects. Extensive numerical experiments corroborate the theoretical findings, demonstrating the control scheme’s practical efficacy.