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<p>This paper addresses the coordinated driving control problem of a six-wheeled lunar rover subject to system uncertainties, external disturbances, and actuator faults. A novel fault-tolerant adaptive control framework is developed using fuzzy logic systems to approximate unknown nonlinear dynamics and fault functions. To mitigate tracking errors, a compensatory control term is integrated into the controller design. A rigorous Lyapunov-based stability analysis demonstrates that the proposed scheme ensures the convergence of tracking errors to a small neighborhood around the origin. Furthermore, the tracking performance can be enhanced by appropriately tuning design parameters. The controller design procedure, including parameter selection guidelines, is explicitly presented through a detailed example. Numerical simulations conducted validate the effectiveness and robustness of the proposed control strategy.</p>

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Adaptive fuzzy fault-tolerant control for coordinated driving of a six-wheel lunar rover with tracking error reduction

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月4日

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  • Duo-Qing Sun,
  • Gong-Li Yang,
  • Shi-Qian He,
  • Yang Chen,
  • Cui-Yi Xiao,
  • Hui-Quan Ma

摘要

This paper addresses the coordinated driving control problem of a six-wheeled lunar rover subject to system uncertainties, external disturbances, and actuator faults. A novel fault-tolerant adaptive control framework is developed using fuzzy logic systems to approximate unknown nonlinear dynamics and fault functions. To mitigate tracking errors, a compensatory control term is integrated into the controller design. A rigorous Lyapunov-based stability analysis demonstrates that the proposed scheme ensures the convergence of tracking errors to a small neighborhood around the origin. Furthermore, the tracking performance can be enhanced by appropriately tuning design parameters. The controller design procedure, including parameter selection guidelines, is explicitly presented through a detailed example. Numerical simulations conducted validate the effectiveness and robustness of the proposed control strategy.