Long Duration Coverage Control of Multiple Robotic Surface Vehicles Under Battery Energy Constraints

IF 15.3 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-06-12 DOI:10.1109/JAS.2023.123438
Shengnan Gao;Zhouhua Peng;Haoliang Wang;Lu Liu;Dan Wang
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Abstract

Dear Editor, This letter addresses long duration coverage problem of multiple robotic surface vehicles (RSVs) subject to battery energy constraints, in addition to uncertainties and disturbances. An anti-disturbance energy-aware control method is proposed for performing coverage task of RSVs. Firstly, a centroidal Voronoi tessellation (CVT) is used to optimize the partition of the given coverage area. The optimal position for each vehicle corresponds to the centroid of the Voronoi cell. Secondly, by consisting two battery energy control barrier functions, an energy-aware kinematic guidance law is designed to drive each RSV to the optimal position. Finally, an anti-disturbance fixed-time kinetic control law is designed for each RSV to track the desired speed based on the fixed-time extended state observer and nonlinear tracking differentiator. By the control method, RSVs are capable of achieving the long duration coverage within the given coverage area. Simulation results verify the effectiveness of the proposed anti-disturbance energy-aware control method for multi-RSV.
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电池能量限制下多个机器人水面飞行器的长时间覆盖控制
亲爱的编辑,这封信讨论了多个机器人水面飞行器(RSV)在电池能量限制以及不确定性和干扰的情况下的长时间覆盖问题。本文提出了一种抗干扰能量感知控制方法,用于执行 RSV 的覆盖任务。首先,使用中心点 Voronoi 网格(CVT)来优化给定覆盖区域的划分。每辆车的最佳位置与 Voronoi 单元的中心点相对应。其次,通过两个电池能量控制障碍函数,设计出一种能量感知运动导向法,将每辆 RSV 驱动到最佳位置。最后,基于固定时间扩展状态观测器和非线性跟踪微分器,为每辆 RSV 设计了抗干扰固定时间动能控制法则,以跟踪所需的速度。通过这种控制方法,RSV 能够在给定的覆盖区域内实现长时间覆盖。仿真结果验证了所提出的多 RSV 抗干扰能量感知控制方法的有效性。
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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来源期刊
Ieee-Caa Journal of Automatica Sinica
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.
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