面向海上搜救的无人潜航器自适应数据驱动协调控制

IF 19.2 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-10-20 DOI:10.1109/JAS.2024.124767

Hao-Liang Wang;De-Zhi Yu;Li-Yu Lu;Zhou-Hua Peng

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引用次数: 0

摘要

亲爱的编辑，这封信是关于多个无人水下航行器（uuv）执行海上搜救（MSR）任务的协调路径跟踪控制方法。每个UUV的动力学模型参数是完全未知的。首先，通过设计垂直视距制导方案，构造运动控制律；其次，设计了一种路径变量更新律，实现了谨慎的多路径控制，实现了对联网无人潜航器的协调控制。此外，uuv可以在预先设计的MSR点自动停止。最后，提出了一种数据驱动的自适应扩展状态观测器（AESO），该观测器在没有先验动力学模型的情况下同时估计未知的总扰动、输入增益和未测速度。通过对某无人潜航器舰队执行MSR的数值模拟，验证了研究结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Adaptive Data-Driven Coordinated Control of UUVs for Maritime Search and Rescue

Dear Editor, This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles (UUVs) to carry out maritime search and rescue (MSR) missions. The kinetic model parameters of each UUV is totally unknown. Firstly, a kinematic control law is constructed by designing a vertical line-of-sight (LOS) guidance scheme. Secondly, a path variable update law is devised to realize careful MSR, which can achieve the coordinated control for networked UUVs. In addition, UUVs could stop at the predesigned MSR points automatically. Finally, a data-driven adaptive extended state observer (AESO) is proposed such that the unknown total disturbance, input gains and unmeasured velocities are simultaneously estimated without a prior kinetic model. The results are verified by numerical simulations for a fleet of UUVs to execute MSR.

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来源期刊

Ieee-Caa Journal of Automatica Sinica Engineering-Control and Systems Engineering

CiteScore

23.50

自引率

11.00%

发文量

880

期刊介绍： The IEEE/CAA Journal of Automatica Sinica is a reputable journal that publishes high-quality papers in English on original theoretical/experimental research and development in the field of automation. The journal covers a wide range of topics including automatic control, artificial intelligence and intelligent control, systems theory and engineering, pattern recognition and intelligent systems, automation engineering and applications, information processing and information systems, network-based automation, robotics, sensing and measurement, and navigation, guidance, and control. Additionally, the journal is abstracted/indexed in several prominent databases including SCIE (Science Citation Index Expanded), EI (Engineering Index), Inspec, Scopus, SCImago, DBLP, CNKI (China National Knowledge Infrastructure), CSCD (Chinese Science Citation Database), and IEEE Xplore.