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Communication Dans Un Congrès Année : 2020

Performance–guaranteed consensus control inspired by the mammalian limbic system for a class of nonlinear multi-agents

Résumé

Computational models of emotional learning observed in the mammalian brain have inspired diverse self-learning control approaches. These architectures are promising in terms of their fast learning ability and low computational cost. In this paper, the objective is to establish performance–guaranteed emotional learning–inspired control (ELIC) strategies for autonomous multi–agent systems (MAS), where each agent incorporates an ELIC structure to support the consensus controller. The objective of each ELIC structure is to identify and compensate model differences between the theoretical assumptions taken into account when tuning the consensus protocol, and the real conditions encountered in the real system to be stabilized. Stability of the closed-loop MAS is demonstrated using a Lyapunov analysis. Simulation results based on the consensus task of a group of inverted pendulums demonstrate the effectiveness of the proposed ELIC for stabilization of nonlinear MAS.

Domaines

Automatique

Dates et versions

hal-03782912 , version 1 (21-09-2022)

Identifiants

Citer

Ignacio Rubio Scola, Luis Rodolfo Garcia Carrillo, João Hespanha, Rogelio Lozano. Performance–guaranteed consensus control inspired by the mammalian limbic system for a class of nonlinear multi-agents. 21st International Federation of Automatic Control World Congress (IFAC WC 2020), Jul 2020, Berlin, Germany. pp.9496-9501, ⟨10.1016/j.ifacol.2020.12.2425⟩. ⟨hal-03782912⟩
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