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<p>This paper investigates the trajectory tracking control of robotic manipulators with parametric uncertainties and external disturbances. A novel predefined-time nonlinear disturbance observer (PTNDO) is proposed to estimate and compensate for both model uncertainties and external disturbances under certain conditions within a user-defined time, addressing the convergence-time limitations of conventional observers. Based on this observer, a predefined-time terminal sliding mode controller (PTTSMC) is designed using a new asymmetric prescribed performance function (PPF). Unlike existing methods that provide only an upper bound on convergence time, the proposed controller ensures exact-time convergence while achieving strict transient performance and high steady-state accuracy. To overcome the vulnerability of prescribed performance control (PPC) under actuator limitations, an adaptive boundary adjustment mechanism is introduced. It employs a smooth triggering condition and a differentiable scaling function to adjust the performance bounds in real time, while maintaining continuity and practical effectiveness. Lyapunov-based analysis guarantees predefined-time stability. Simulation and experimental results confirm that the proposed PTTSMC framework, combining PTNDO and adaptive PPC, ensures excellent transient performance and tracking precision, demonstrating robustness and practical applicability.</p>

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Trajectory tracking control for robotic manipulators with prescribed performance based on predefined-time disturbance observer

  • 期刊论文

  • 发表日期：

    2025年8月4日

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  • Jianjun Zhang,
  • Manjiang Xia,
  • Zhonghua Wu,
  • Qunpo Liu,
  • Xuhui Bu,
  • Juan Shi

摘要

This paper investigates the trajectory tracking control of robotic manipulators with parametric uncertainties and external disturbances. A novel predefined-time nonlinear disturbance observer (PTNDO) is proposed to estimate and compensate for both model uncertainties and external disturbances under certain conditions within a user-defined time, addressing the convergence-time limitations of conventional observers. Based on this observer, a predefined-time terminal sliding mode controller (PTTSMC) is designed using a new asymmetric prescribed performance function (PPF). Unlike existing methods that provide only an upper bound on convergence time, the proposed controller ensures exact-time convergence while achieving strict transient performance and high steady-state accuracy. To overcome the vulnerability of prescribed performance control (PPC) under actuator limitations, an adaptive boundary adjustment mechanism is introduced. It employs a smooth triggering condition and a differentiable scaling function to adjust the performance bounds in real time, while maintaining continuity and practical effectiveness. Lyapunov-based analysis guarantees predefined-time stability. Simulation and experimental results confirm that the proposed PTTSMC framework, combining PTNDO and adaptive PPC, ensures excellent transient performance and tracking precision, demonstrating robustness and practical applicability.