基于多智能体系统的水下航行器编队控制

IF 1.2 4区 计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS
Dr. Bikramaditya Das, B. B. Pati
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引用次数: 3

摘要

本文提出了一种基于自主移动智能体的多声水下航行器编队控制算法。采用分布式共识协调算法,开发了一种鲁棒跟踪算法,保证了水下机器人之间的信息传递。基于多智能体系统的特点,鲁棒寻迹技术的发展是为了解决各智能体的不完全信息能力,如计算异步、数据分散、无系统全局控制等。在不可靠的窄带水声介质中,在恒定或变化的虚拟leader速度下,可以实现基于auv的分布式协调一致跟踪。在此基础上,将基于虚拟领航器速度实现跟踪的研究扩展到固定网络拓扑和交换网络拓扑。同样,对于轻度连接,定义邻接矩阵,以确保auv之间的自适应连接。基于共识跟踪的恒定虚拟领先车辆速度方法由于不需要精确的位置和速度测量,在减小误差方面具有更强的鲁棒性。利用MATLAB进行了仿真,并对仿真结果进行了分析,以实现水下通信约束条件下的有效编队控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Formation control of underwater vehicles using Multi Agent System
This paper proposes the development of a formation control algorithm of multiple acoustic underwater vehicles by employing the behaviour of autonomous mobile agents under a proposed pursuit. A robust pursuit is developed using the distributed consensus coordinated algorithm ensuring the transfer of information among the AUVs. The development of robust pursuit based on characteristics of multi-agent system is for solving the incomplete information capabilities in each agent such as asynchronous computation, decentralized data and no system global control. In unreliable and narrow banded underwater acoustic medium, the formation of AUVs based distributed coordinated consensus tracking can be accomplished under the constant or varying virtual leader’s velocity. Further, the study to achieve tracking based on virtual leader AUV’s velocity is extended to fixed and switching network topologies. Again for mild connectivity, an adjacency matrix is defined in such a way that an adaptive connectivity is ensured between the AUVs. The constant virtual leader vehicle velocity method based on consensus tracking is more robust to reduce inaccuracy because no accurate position and velocity measurements are required. Results were obtained using MATLAB and acquired outcomes are analysed for efficient formation control in presence of the underwater communication constraints.
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来源期刊
Archives of Control Sciences
Archives of Control Sciences Mathematics-Modeling and Simulation
CiteScore
2.40
自引率
33.30%
发文量
0
审稿时长
14 weeks
期刊介绍: Archives of Control Sciences welcomes for consideration papers on topics of significance in broadly understood control science and related areas, including: basic control theory, optimal control, optimization methods, control of complex systems, mathematical modeling of dynamic and control systems, expert and decision support systems and diverse methods of knowledge modelling and representing uncertainty (by stochastic, set-valued, fuzzy or rough set methods, etc.), robotics and flexible manufacturing systems. Related areas that are covered include information technology, parallel and distributed computations, neural networks and mathematical biomedicine, mathematical economics, applied game theory, financial engineering, business informatics and other similar fields.
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