武汉理工大学学报(交通科学与工程版)2024,Vol.48Issue(6) :1111-1118.DOI:10.3963/j.issn.2095-3844.2024.06.015

基于控制障碍函数的多艇协同包围控制方法

Cooperative Encircling Control Method of Multiple Unmanned Vehicles Based on Control Barrier Functions

卢泰宇 徐海祥 余文曌
武汉理工大学学报(交通科学与工程版)2024,Vol.48Issue(6) :1111-1118.DOI:10.3963/j.issn.2095-3844.2024.06.015

基于控制障碍函数的多艇协同包围控制方法

Cooperative Encircling Control Method of Multiple Unmanned Vehicles Based on Control Barrier Functions

卢泰宇 1徐海祥 1余文曌1
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作者信息

  • 1. 武汉理工大学高性能船舶技术教育部重点实验室 武汉 430063;武汉理工大学船海与能源动力工程学院 武汉 430063
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摘要

文中提出了一种基于控制障碍函数的分层控制方法.在制导层设计了一种仅需邻居艇信息的分布式制导律,实现对运动目标的包围控制,并引入控制障碍函数,保证相邻两艇在规避静态障碍物的同时始终在通信范围内;考虑未知环境干扰、模型不确定性以及由传统滑模控制器所产生的抖振现象,基于复合正交神经网络的逼近特性和自适应滑模趋近律,在控制层设计了自适应神经滑模控制律,以精确跟踪分布式制导律给出的制导信号;基于Lyapunov函数证明了上述闭环控制系统的稳定性,并进行了仿真对比.结果表明:所提出的控制方法能有效提高多无人艇在障碍环境下执行包围任务的成功率,并使控制输出更平滑.

Abstract

A hierarchical control method based on control obstacle function was proposed,and a distrib-uted guidance law was designed at the guidance layer to realize the encirclement control of moving tar-gets only by the information of neighboring boats.The control obstacle function was introduced to en-sure that two adjacent boats were always in the communication range while avoiding static obstacles.Considering the disturbance of unknown environment,model uncertainty and chattering caused by tra-ditional sliding mode controller,an adaptive neural sliding mode control law was designed at the con-trol layer based on the approximation characteristics of compound orthogonal neural network and a-daptive sliding mode reaching law to accurately track the guidance signal given by distributed guidance law.The stability of the closed-loop control system was proved based on Lyapunov function,and the simulation results show that the proposed control method can effectively improve the success rate of multi-unmanned boats in the obstacle environment and make the control output smoother.

关键词

无人艇/协同包围控制/多智能体系统/避障/控制障碍函数/自适应神经滑模控制

Key words

unmanned surface vehicles/cooperative encircling control/multi agent system/obstacles avoidance/control barrier functions/adaptive neural sliding mode control

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出版年

2024
武汉理工大学学报(交通科学与工程版)
武汉理工大学

武汉理工大学学报(交通科学与工程版)

CSTPCD
影响因子:0.462
ISSN:2095-3844
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