不可靠通信拓扑下多欧拉-拉格朗日系统弹性无碰撞分布式最优协调。

IF 9.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Jia-Yuan Yin,Guang-Hong Yang,Huimin Wang
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引用次数: 0

摘要

本文研究了不可靠通信拓扑下多个欧拉-拉格朗日系统的弹性避碰分布式最优协调问题。由于恶劣的网络条件和网络攻击,代理之间的通信可能会在一定的时间间隔内中断。为了实现agent间的避碰,重新设计了屏障函数,并提出了基于通信的分布式避碰算法。然后,引入了一种基于实时位置梯度的弹性避碰DOC策略,该策略结合了用于生成避碰编队参考信号的协调器和自适应跟踪控制器。利用Lyapunov方法和有界性分析,证明了所提出的DOC策略即使在不可靠的通信网络下也能实现收敛和避免碰撞。最后,通过仿真算例验证了所提策略的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Resilient Collision-Free Distributed Optimal Coordination for Multiple Euler-Lagrangian Systems Under Unreliable Communication Topologies.
This article addresses the problem of resilient collision avoidance distributed optimal coordination (DOC) for multiple Euler-Lagrangian (EL) systems under unreliable communication topologies. Due to adverse network conditions and cyber attacks, communication between agents can be disrupted during certain time intervals. To achieve collision avoidance between agents, a barrier function is redesigned, and a communication-based distributed collision avoidance algorithm is correspondingly proposed. Then, a resilient collision avoidance DOC strategy based on real-time position-based gradient is introduced, incorporating a coordinator for generating collision avoidance formation reference signals and an adaptive tracking controller. By utilizing the Lyapunov method and boundedness analysis, the proposed DOC strategy is proven to achieve both convergence and collision avoidance, even under unreliable communication networks. Finally, the effectiveness of the proposed strategy is validated through a simulation example.
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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