Data-Based System Representation and Synchronization for Multiagent Systems
Victor G. Lopez, Matthias A. Müller
TL;DR
The paper addresses data-based synchronization for continuous-time multiagent systems, covering homogeneous and heterogeneous dynamics without relying on full plant models. It leverages Willems-type data representations and persistently exciting trajectories to formulate data-driven control laws. For homogeneous agents, it reports LMIs that yield distributed static controllers, ensuring asymptotic synchronization to a leader. For heterogeneous agents, it develops fully data-based dynamic controllers that guarantee convergence using only measured data and without model knowledge, validated by simulations. The work advances practical synchronization by enabling model-free design and data-driven stability guarantees in both homogeneous and heterogeneous multiagent networks.
Abstract
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.