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Data-Based System Representation and Synchronization for Multiagent Systems
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This paper presents novel solutions of the data-based synchronization problem for continuous-time multiagent systems. We consider the cases of homogeneous and heterogeneous systems. First, we obtain a data-based representation of the synchronization error dynamics for homogeneous systems and show how to extend existing data-based stabilization results to stabilize such error dynamics. The proposed method relies on the solution of a set of linear matrix inequalities that are shown to be feasible. Then, we solve the synchronization problem for heterogeneous systems by means of dynamic controllers. Different from existing results, we do not require model knowledge for the followers and the leader. The theoretical results are finally validated using a numerical simulation.
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Data-driven Internal Model Control for Output Regulation
A data-driven internal model controller achieves zero or kth-order asymptotic output regulation for unknown linear, nonlinear, and multi-agent systems without solving regulation equations.
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