Collision avoidance time-varying group formation tracking control for multi-agent systems

IF 3.4 2区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Weihao Li, Shiyu Zhou, Mengji Shi, Jiangfeng Yue, Boxian Lin, Kaiyu Qin
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Abstract

This study considers the time-varying group formation (TVGF) tracking control problem for general linear multi-agent systems (MASs) with collision avoidance, where the MAS is divided into multiple subgroups, enabling followers to form prescribed formations and track trajectories provided by their respective leaders without collisions. Firstly, a distributed TVGF tracking control protocol is introduced using only relative information among neighboring agents. Then, feasibility conditions under which MASs can successfully realize the TVGF tracking without collisions are put forward. Utilizing Lyapunov stability theory, the convergence of the TVGF tracking error systems is confirmed, ensuring the collision-free achievement of the desired formation. Finally, some simulation examples are provided to validate the effectiveness of the theoretical results.

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来源期刊
Applied Intelligence
Applied Intelligence 工程技术-计算机:人工智能
CiteScore
6.60
自引率
20.80%
发文量
1361
审稿时长
5.9 months
期刊介绍: With a focus on research in artificial intelligence and neural networks, this journal addresses issues involving solutions of real-life manufacturing, defense, management, government and industrial problems which are too complex to be solved through conventional approaches and require the simulation of intelligent thought processes, heuristics, applications of knowledge, and distributed and parallel processing. The integration of these multiple approaches in solving complex problems is of particular importance. The journal presents new and original research and technological developments, addressing real and complex issues applicable to difficult problems. It provides a medium for exchanging scientific research and technological achievements accomplished by the international community.
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