Data-driven adaptive consensus for linear multi-agent systems: A scalable distributed protocol

IF 4.8 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica Pub Date : 2025-01-16 DOI:10.1016/j.automatica.2025.112126

Wenying Xu , Zidong Wang , Shaofu Yang , Wenwu Yu

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引用次数: 0

Abstract

This paper is concerned with the noiseless and noisy data-driven consensus problem of general linear multi-agent systems (MASs) with unknown agent dynamics. First, a data-driven adaptive scheme is designed to enable each edge to tune its weight in an on-line fashion. Subsequently, a distributed noiseless data-driven adaptive consensus (DDAC) protocol is established for the MASs so as to ensure guaranteed consensus. In this protocol, agents communicate with their neighbors through an undirected and connected graph. Importantly, this protocol is proven to be independent of both system model knowledge and be scalable with respect to the size of communication network. Moreover, to address the scenario of a directed communication graph, a modified node-based adaptive scheme, which relies solely on data, is introduced, along with a refined DDAC protocol. The conditions for achieving consensus are derived as semi-definite programs, and the corresponding feasibility is analyzed. Furthermore, the paper considers a noisy data scenario and tackles the consensus problem with a noisy data by employing a refined adaptive scheme and establishing a distributed noisy DDAC protocol. Compared to existing consensus protocols, our DDAC protocol offers high flexibility and scalability by eliminating the need for a system model and global network information. Finally, three examples are provided to verify the effectiveness of the proposed DDAC protocols.

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来源期刊

Automatica 工程技术-工程：电子与电气

CiteScore

10.70

自引率

7.80%

发文量

617

审稿时长

5 months

期刊介绍： Automatica is a leading archival publication in the field of systems and control. The field encompasses today a broad set of areas and topics, and is thriving not only within itself but also in terms of its impact on other fields, such as communications, computers, biology, energy and economics. Since its inception in 1963, Automatica has kept abreast with the evolution of the field over the years, and has emerged as a leading publication driving the trends in the field. After being founded in 1963, Automatica became a journal of the International Federation of Automatic Control (IFAC) in 1969. It features a characteristic blend of theoretical and applied papers of archival, lasting value, reporting cutting edge research results by authors across the globe. It features articles in distinct categories, including regular, brief and survey papers, technical communiqués, correspondence items, as well as reviews on published books of interest to the readership. It occasionally publishes special issues on emerging new topics or established mature topics of interest to a broad audience. Automatica solicits original high-quality contributions in all the categories listed above, and in all areas of systems and control interpreted in a broad sense and evolving constantly. They may be submitted directly to a subject editor or to the Editor-in-Chief if not sure about the subject area. Editorial procedures in place assure careful, fair, and prompt handling of all submitted articles. Accepted papers appear in the journal in the shortest time feasible given production time constraints.