Adaptive Cooperative Tracking and Parameter Estimation of an Uncertain Leader Over General Directed Graphs

• 成果类型: Article
• 署名作者: Wang, Shimin; Zhang, Hongwei; Chen, Zhiyong
• 署名单位: Queens University - Canada; Harbin Institute of Technology; University of Newcastle
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3197670
• 发表日期: 2023
• 页码: 3888-3901
• 关键词: Directed graph; leader-following consen-sus; Multiagent system (MAS); Parameter Estimation; un-certain leader

摘要

This article studies the cooperative tracking problem of heterogeneous Euler-Lagrange systems with an uncertain leader. Different from most existing works, system dynamic knowledge of the leader node is unaccessible to any follower node in our article. Distributed adaptive observers are designed for all follower nodes to simultaneously estimate the state and parameters of the leader node. The observer design does not rely on the frequency knowledge of the leader node, and the estimation errors are shown to converge to zero exponentially. Moreover, the results are applied to general directed graphs, where the symmetry of Laplacian matrix does not hold. This is due to two newly developed Lyapunov equations, which solely depend on communication network topologies. Interestingly, using these Lyapunov equations, many results of multiagent systems over undirected graphs can be extended to general directed graphs. Finally, this article also advances the knowledge base of adaptive control systems by providing a main tool in the analysis of parameter convergence for adaptive observers.