Scholarlink

<p>This study addresses the design of an adaptive funnel control strategy for a class of uncertain nonlinear systems represented in a non-strict feedback form. The systems under consideration are affected by input saturation, which can compromise control performance or potentially destabilize the system. To tackle this issue, a smooth compensation mechanism is incorporated. By integrating the backstepping design technique with Lyapunov-based stability analysis and the funnel control concept, an adaptive funnel tracking controller is developed using the function approximation capabilities of multi-dimensional Taylor networks (MTNs). Rigorous Lyapunov analysis confirms the stability of the closed-loop system, ensuring that all signals remain semi-globally uniformly ultimately bounded (SGUUB). Moreover, the system output effectively tracks the desired reference trajectory, maintaining the tracking error within a predefined funnel throughout both transient and steady-state responses and converging to a target interval specified by the funnel function. The effectiveness and advantages of the proposed method are illustrated through two simulation examples.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Adaptive Control Based on Multi-Dimensional Taylor Networks for Uncertain Nonlinear Systems under Input Saturation Using a Funnel Constraint Function

  • 期刊论文

  • 发表日期：

    2026年3月11日

查看全文
  • Arun Bali,
  • Uday Pratap Singh,
  • Muhammad Maaruf

摘要

This study addresses the design of an adaptive funnel control strategy for a class of uncertain nonlinear systems represented in a non-strict feedback form. The systems under consideration are affected by input saturation, which can compromise control performance or potentially destabilize the system. To tackle this issue, a smooth compensation mechanism is incorporated. By integrating the backstepping design technique with Lyapunov-based stability analysis and the funnel control concept, an adaptive funnel tracking controller is developed using the function approximation capabilities of multi-dimensional Taylor networks (MTNs). Rigorous Lyapunov analysis confirms the stability of the closed-loop system, ensuring that all signals remain semi-globally uniformly ultimately bounded (SGUUB). Moreover, the system output effectively tracks the desired reference trajectory, maintaining the tracking error within a predefined funnel throughout both transient and steady-state responses and converging to a target interval specified by the funnel function. The effectiveness and advantages of the proposed method are illustrated through two simulation examples.