Consensus for agents with general dynamics using optimistic optimization
Résumé
An important challenge in multiagent systems is consensus, in which the agents must agree on certain controlled variables of interest. So far, most consensus algorithms for agents with nonlinear dynamics exploit the specific form of the nonlinearity. Here, we propose an approach that only requires a black-box simulation model of the dynamics, and is therefore applicable to a very wide class of nonlinearities. This approach works for agents communicating in a fixed, connected network. It first designs a reference behavior with a classical consensus protocol, and then finds control actions that drive the nonlinear agents towards this behavior, using a recent optimistic optimization algorithm. By exploiting the guarantees of optimistic optimization, we prove that the agents achieve practical consensus. A representative example is further analyzed, and simulation results on nonlinear robotic arms are provided.
Domaines
Automatique
Origine : Fichiers produits par l'(les) auteur(s)
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