Suppr超能文献

网络化全驱动自主水面舰艇的分布式无模型编队控制

Distributed model-free formation control of networked fully-actuated autonomous surface vehicles.

作者信息

Niu Xiaobing, Gao Shengnan, Xu Zhibin, Feng Shiliang

机构信息

School of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.

China State Shipbuilding Corporation Limited, Beijing, China.

出版信息

Front Neurorobot. 2022 Sep 29;16:1028656. doi: 10.3389/fnbot.2022.1028656. eCollection 2022.

Abstract

This paper presents a distributed constant bearing guidance and model-free disturbance rejection control method for formation tracking of autonomous surface vehicles subject to fully unknown kinetic model. First, a distributed constant bearing guidance law is designed at the kinematic level to achieve a consensus task. Then, by using an adaptive extended state observer (AESO) to estimate the total uncertainties and unknown input coefficients, a simplified model-free kinetic controller is designed based on a dynamic surface control (DSC) design. It is proven that the closed-loop system is input-to-state stable The stability of the closed-loop system is established. A salient feature of the proposed method is that a cooperative behavior can be achieved without knowing any priori information. An application to formation control of autonomous surface vehicles is given to show the efficacy of the proposed integrated distributed constant bearing guidance and model-free disturbance rejection control.

摘要

本文提出了一种用于自主水面舰艇编队跟踪的分布式恒向制导和无模型干扰抑制控制方法,该方法适用于完全未知动力学模型的情况。首先,在运动学层面设计了一种分布式恒向制导律,以实现一致性任务。然后,通过使用自适应扩张状态观测器(AESO)来估计总不确定性和未知输入系数,基于动态面控制(DSC)设计了一种简化的无模型动力学控制器。证明了闭环系统是输入到状态稳定的,建立了闭环系统的稳定性。该方法的一个显著特点是,无需任何先验信息即可实现协同行为。给出了该方法在自主水面舰艇编队控制中的应用,以展示所提出的集成分布式恒向制导和无模型干扰抑制控制的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6999/9558738/7cce678d73cb/fnbot-16-1028656-g0001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验