Abstract
In this paper, we consider consensus problem of high-order multi-agent systems with non-identical unknown nonlinear dynamics. Linearly parameterized models are used to describe the unknown nonlinear dynamics of all agents. Based on the relative state measurements, a class of adaptive consensus scheme is designed for each follower in networks with directed switching topologies. Analysis of stability and parameter convergence is conducted based on Lyapunov theory, algebraic graph theory, M-matrix theory. An example is given to demonstrate the effectiveness of the proposed adaptive control algorithms.
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