Output Feedback Cooperative-Antagonistic Average Consensus in High-Order Multiagent Systems Over Directed Graphs.

IF 11.3 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Xiaohua Ge, Dario Giuseppe Lui, Alberto Petrillo, Stefania Santini
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引用次数: 0

Abstract

Output average consensus of cooperative/ cooperative-antagonistic multiagent systems (MASs) is of great significance in the engineering field, but is rarely addressed for general linear high-order networks interacting over directed graphs. This problem is herein tackled and solved via a novel hierarchical distributed output feedback control architecture, where the higher level embeds a distributed reference generator while the lower one is characterized by a proportional-integral-derivative (PID)-like control structure. The former is responsible for gathering the networked information to compute the output average agreement, which is exploited by the latter for the achievement of the coordination task. Combining the regulator equations and the static output feedback (SOF) procedure, properly extended in the distributed context, a well-defined closed-loop network is derived, and the control gain tuning procedure is provided. The versatility of the proposed approach in also handling the heterogeneous case, arising when agents do not share the same dynamical model, is also proved. Theoretical results establish the stability conditions via the Lyapunov-based analysis and the input-to-state stability (ISS) theory, and prove the accomplishment of the output unsigned/signed average consensus objectives with transient and steady-state performance improvements. Illustrative examples further corroborate the validity of the theoretical results.

有向图上高阶多智能体系统的输出反馈合作-对抗平均一致性。
合作/合作-对抗多智能体系统(MASs)的输出平均一致性在工程领域具有重要意义,但很少涉及有向图上相互作用的一般线性高阶网络。本文通过一种新颖的分层分布式输出反馈控制体系结构来解决这个问题,其中高层嵌入了一个分布式参考发生器,而低层则采用了类似于比例积分导数(PID)的控制结构。前者负责收集网络信息来计算输出的平均协议,后者利用该平均协议来完成协调任务。结合稳压器方程和静态输出反馈(SOF)过程,在分布式环境下进行适当扩展,导出了一个定义良好的闭环网络,并给出了控制增益整定过程。本文还证明了该方法在处理agent不共享同一动态模型时所产生的异构情况时的通用性。理论结果通过基于lyapunov的分析和输入-状态稳定性(ISS)理论建立了稳定性条件,并证明了输出无符号/有符号平均共识目标在瞬态和稳态性能改进下的实现。算例进一步证实了理论结果的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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