Scholarlink

<p>This paper investigates the formation tracking control problem for multiple unmanned surface vehicles (USVs) under prescribed performance constraints in the presence of model uncertainties and unknown disturbances. A decentralized formation control strategy is developed based on a modified active disturbance rejection control (ADRC) framework, where a model-compensation extended state observer (ESO) is designed to estimate the total disturbance and enhance robustness. To avoid the “explosion of complexity”, a tracking differentiator (TD) is employed to approximate virtual control derivatives, while a universal barrier function (UBF) is incorporated into the Lyapunov-based synthesis to guarantee both transient and steady-state performance bounds. Rigorous Lyapunov analysis proves that all closed-loop signals remain uniformly ultimately bounded, prescribed performance constraints are strictly satisfied, and inter-agent collision avoidance and communication connectivity are maintained. Comprehensive simulations further demonstrate significant performance advantages over representative baseline methods. In particular, the proposed controller achieves a 57.4% reduction in IAE and a 42.6% reduction in RMSE compared with a PID controller, and a further 49.4% and 36.7% reduction relative to a backstepping controller. These quantitative results confirm the superior accuracy and robustness of the proposed approach.</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

Formation tracking control of multiple USVs using ADRC with prescribed performance

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月28日

查看全文
  • Mingen Huo,
  • Wenlong Mao,
  • Xiaojuan Wang

摘要

This paper investigates the formation tracking control problem for multiple unmanned surface vehicles (USVs) under prescribed performance constraints in the presence of model uncertainties and unknown disturbances. A decentralized formation control strategy is developed based on a modified active disturbance rejection control (ADRC) framework, where a model-compensation extended state observer (ESO) is designed to estimate the total disturbance and enhance robustness. To avoid the “explosion of complexity”, a tracking differentiator (TD) is employed to approximate virtual control derivatives, while a universal barrier function (UBF) is incorporated into the Lyapunov-based synthesis to guarantee both transient and steady-state performance bounds. Rigorous Lyapunov analysis proves that all closed-loop signals remain uniformly ultimately bounded, prescribed performance constraints are strictly satisfied, and inter-agent collision avoidance and communication connectivity are maintained. Comprehensive simulations further demonstrate significant performance advantages over representative baseline methods. In particular, the proposed controller achieves a 57.4% reduction in IAE and a 42.6% reduction in RMSE compared with a PID controller, and a further 49.4% and 36.7% reduction relative to a backstepping controller. These quantitative results confirm the superior accuracy and robustness of the proposed approach.