Adaptive consensus of multi-agents in networks with jointly connected topologies

• Published in: Automatica (Oxford) Vol. 48; no. 8; pp. 1783 - 1790
• Main Authors: Yu, Hui, Xia, Xiaohua
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.08.2012; Elsevier
• Subjects: Adaptive control; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Consensus; Control system analysis; Control system synthesis; Control theory. Systems; Exact sciences and technology; Jointly connected topology; Multi-agent systems; Parameter convergence; Software; Parameter convergence; Jointly connected topology; Adaptive control; Consensus; Multi-agent systems; Leadership; Stability; Position control; Lyapunov method; Control synthesis; Graph theory; Distributed system; Parameterization; Adaptive method; Intelligent agent; Multiagent system; Network topology; Leader election; Artificial intelligence; Lyapunov function
• ISSN: 0005-1098; 1873-2836
• DOI: 10.1016/j.automatica.2012.05.068

In this paper, the consensus problem of multi-agent following a leader is studied. An adaptive design method is presented for multi-agent systems with non-identical unknown nonlinear dynamics, and for a leader to be followed that is also nonlinear and unknown. By parameterizations of unknown nonlinear dynamics of all agents, a decentralized adaptive consensus algorithm is proposed in networks with jointly connected topologies by incorporating local consensus errors in addition to relative position feedback. Analysis of stability and parameter convergence of the proposed algorithm are conducted based on algebraic graph theory and Lyapunov theory. Finally, examples are provided to validate the theoretical results.