Abstract
In this paper, a novel model-free adaptive bipartite consensus control scheme is proposed for unknown heterogeneous nonlinear multi-agent systems (MASs) with different input delays. Firstly, an equivalent data model is established for each agent by using the dynamic linearisation method. Secondly, based on an established equivalent data model and constructed predictive compensation algorithm, the distributed model-free adaptive bipartite consensus control scheme (DMFABCC) is designed by only utilising the measured input/output data rather than the state-space model of MASs. Next, by selecting an appropriate Lyapunov function, the convergence of bipartite tracking error is rigorously proved. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed DMFABCC scheme for achieving the bipartite consensus target.
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