Abstract
This paper investigates the adaptive consensus problem for multi-agent systems with unknown nonlinear dynamics. The topologies of the networks are jointly connected. An adaptive consensus algorithm is proposed by using linear parameterizations of unknown nonlinear dynamics of all agents. By stability analysis and parameter convergence analysis of the proposed algorithm, adaptive consensus can be realized based on neighboring graphs. The stability analysis is based on algebraic graph theory and Lyapunov theory, the PE condition plays a key role in parameter convergence analysis. The simulation results are provided to demonstrate the effectiveness of our theoretical results.
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Liu, G., Yu, H., Zhang, Y. (2013). Adaptive Consensus of Multi-agents in Jointly Connected Networks. In: Yang, Y., Ma, M., Liu, B. (eds) Information Computing and Applications. ICICA 2013. Communications in Computer and Information Science, vol 391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53932-9_3
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DOI: https://doi.org/10.1007/978-3-642-53932-9_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-53931-2
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