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<p>In this paper, a fixed-time tracking control method is proposed for uncertain nonlinear systems with prescribed performance and full-state constraints. The proposed approach utilizes novel adaptive laws based on fuzzy systems to handle uncertain nonlinearities and disturbances. To improve convergence efficiency, a fixed-time command filter is employed to address the “complexity explosion” problem. Subsequently, a fixed-time tracking control scheme is developed by combining prescribed performance control (PPC) with the barrier Lyapunov function (BLF) methodology. The proposed method not only guarantees that the output tracking error converges to a predefined performance region within a fixed time but also ensures that all system states remain within their constraint boundaries, with the settling time being independent of the initial conditions. Simulation results from both a numerical example and a single-link robotic manipulator system demonstrate the effectiveness of the proposed controller.</p>

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Fixed-Time Adaptive Fuzzy Tracking Control for Uncertain Nonlinear Systems with Prescribed Performance and Full-State Constraints

  • 期刊论文

  • 发表日期：

    2025年8月11日

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  • Xiaohong Cheng,
  • Shuang Liu,
  • Shaomeng Gu,
  • Wenbo Wang,
  • Cong Zhang

摘要

In this paper, a fixed-time tracking control method is proposed for uncertain nonlinear systems with prescribed performance and full-state constraints. The proposed approach utilizes novel adaptive laws based on fuzzy systems to handle uncertain nonlinearities and disturbances. To improve convergence efficiency, a fixed-time command filter is employed to address the “complexity explosion” problem. Subsequently, a fixed-time tracking control scheme is developed by combining prescribed performance control (PPC) with the barrier Lyapunov function (BLF) methodology. The proposed method not only guarantees that the output tracking error converges to a predefined performance region within a fixed time but also ensures that all system states remain within their constraint boundaries, with the settling time being independent of the initial conditions. Simulation results from both a numerical example and a single-link robotic manipulator system demonstrate the effectiveness of the proposed controller.