Direct Adaptive Cooperative Output Regulation of Unknown Multiagent Systems via Distributed Internal Model
成果类型：
Article
署名作者：
Lin, Liquan; Huang, Jie
署名单位：
Chinese University of Hong Kong
刊物名称：
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
ISSN/ISSBN：
0018-9286
DOI：
10.1109/TAC.2025.3576180
发表日期：
2025
关键词：
摘要：
The existing result on the cooperative output regulation problem for unknown linear multiagent systems using the data-driven distributed internal model approach is limited to the case where each follower is a single-input and single-output system, and the communication network among all agents is an acyclic static digraph. In this article, we further address the same problem for unknown linear multiagent systems with multi-input and multi-output followers over a general static and connected digraph by a value iteration approach. Further, we make two main improvements over the existing result. First, compared with the existing approach, we reduce the number of the unknown variables governed by a sequence of linear algebraic equations. Second, we show that the sequence of linear algebraic equations can be further decoupled to two sequences of lower dimensional linear algebraic equations. As a result, our approach not only drastically reduces the computational cost but also significantly weakens the solvability conditions. A numerical example is used to illustrate the effectiveness of our approach.