有通信延迟和无通信延迟的分数阶多代理系统基于被动性的编队控制

IF 5.3 3区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jin-Liang Wang;Lina Huang;Shun-Yan Ren;Tingwen Huang
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引用次数: 0

摘要

由于分数阶微分方程可以更精确地模拟代理的动态,因此研究分数阶多代理系统(FOMAS)的编队控制非常有意义。最近,由于被动系统具有内部稳定性,因此被动性被广泛用于解决整阶多代理系统的各种合作控制问题。显然,基于被动性处理 FOMAS 的编队控制问题也很有优势。本文利用被动性讨论了二阶非线性 FOMAS 的两种编队控制问题,即分别是无通信延迟和有通信延迟的情况。在所设计的状态反馈和自适应状态反馈控制器的基础上,推导出了几种单分阶代理的被动性条件。此外,通过选择合适的分布式状态反馈控制策略和利用分数阶代理的被动性,给出了 FOMAS 的两个形成标准。此外,上述结果还进一步扩展到了控制输入存在通信延迟的情况。最后,还提供了两个数值示例,以证实推导出的形成准则的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Passivity-Based Formation Control for Fractional-Order Multiagent Systems With and Without Communication Delay
Because fractional-order differential equations can more accurately model the dynamics of agents, it is very meaningful to investigate the formation control for fractional-order multi-agent systems (FOMASs). Recently, passivity has been widely utilized to tackle various cooperative control problems for integer-order MASs since passive systems are internally stable. Apparently, it is also advantageous to deal with the formation control problem of FOMASs based on the passivity. In this paper, two types of formation control problems for second-order nonlinear FOMASs are discussed by employing the passivity, that is, the cases without and with communication delay, respectively. On the basis of the devised state feedback and adaptive state feedback controllers, several passivity conditions for single fractional-order agent are derived. Furthermore, by selecting suitable distributed state feedback control strategy and exploiting the passivity of fractional-order agent, two formation criteria for the FOMAS are given. In addition, the above obtained results are further extended to the case where communication delay exists in the control input. Finally, two numerical examples are provided to substantiate the effectiveness of the derived formation criteria.
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来源期刊
CiteScore
10.30
自引率
7.50%
发文量
147
期刊介绍: The IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI) publishes original articles on emerging aspects of computational intelligence, including theory, applications, and surveys. TETCI is an electronics only publication. TETCI publishes six issues per year. Authors are encouraged to submit manuscripts in any emerging topic in computational intelligence, especially nature-inspired computing topics not covered by other IEEE Computational Intelligence Society journals. A few such illustrative examples are glial cell networks, computational neuroscience, Brain Computer Interface, ambient intelligence, non-fuzzy computing with words, artificial life, cultural learning, artificial endocrine networks, social reasoning, artificial hormone networks, computational intelligence for the IoT and Smart-X technologies.
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