Aller au contenu principal
Accès ouvert déclaré 2025 article

High-order consensus: Optimal controller design

0Citations signalées — pas une note de qualité
1Institutions déclarées
1Pays d’affiliation déclarés

Résumé fourni par la source

This paper considers the optimal design of a high-order consensus protocol applied to agents modeled with multiple integrators. The problem addressed amounts to determining the optimal values for the coupling gains and for the edge weights of the directed graph that models the network. With that goal in mind, an LQR-like cost function is proposed, which is obtained from the typical LQR cost function by taking the expectation over the initial state of the system. To enable the implementation of optimization algorithms, and ultimately solve the considered problem, it is first necessary to tackle the evaluation of the cost and its derivatives, taking into account the particularities of the consensus problem. Then, to determine the optimal parameters of the high-order consensus protocol, a truncated Newton method is considered. Furthermore, a suboptimal design approach is proposed, which consists in splitting the problem into two simpler ones that are solved sequentially, in a reduced amount of time. It is also shown that if one considers symmetric Laplacian matrices, these simpler problems are convex for second- and third-order consensus under a mild assumption on the initial conditions. Finally, the proposed algorithms are illustrated with examples that demonstrate their efficacy as well as the benefits to the controller synthesis.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
High-order consensus: Optimal controller design
Date Crossref
01/05/2025
Éditeur
Elsevier BV
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

Institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Sujets associés

Distributed Control Multi-Agent SystemsNeural Networks Stability and SynchronizationStability and Control of Uncertain Systems

BNTIC News n’est pas le producteur de ces données. Recherche à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, ROR et la Banque mondiale, sans clé ; OpenAlex reste optionnel. Aucun service payant requis, aucune donnée externe enregistrée en base. Sources et limites.