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dc.contributor.author
Rubio Scola, Ignacio Eduardo Jesus
dc.contributor.author
Garcia Carrillo, Luis Rodolfo
dc.contributor.author
Hespanha, Joao P.
dc.date.available
2023-02-07T11:32:50Z
dc.date.issued
2022-01
dc.identifier.citation
Rubio Scola, Ignacio Eduardo Jesus; Garcia Carrillo, Luis Rodolfo; Hespanha, Joao P.; Limbic System-Inspired Performance-Guaranteed Control for Nonlinear Multi-Agent Systems With Uncertainties; Institute of Electrical and Electronics Engineers; IEEE Transactions on Neural Networks and Learning Systems; 1-2022; 1-12
dc.identifier.issn
2162-237X
dc.identifier.uri
http://hdl.handle.net/11336/187098
dc.description.abstract
We introduce a performance-guaranteed limbic system-inspired control (LISIC) strategy for nonlinear multi-agent systems (MASs) with uncertain high-order dynamics and external perturbations, where each agent in the MAS incorporates a LISIC structure to support the consensus controller. This novel approach, which we call double integrator LISIC (DILISIC), is designed to imitate double integrator dynamics after closing the agent-specific control loop, allowing the control designer to apply consensus techniques specifically formulated for double integrator agents. The objective of each DILISIC structure is then to identify and compensate model differences between the theoretical assumptions considered when tuning the consensus protocol and the actual conditions encountered in the real-time system to be controlled. A Lyapunov analysis is provided to demonstrate the stability of the closed-loop MAS enhanced with the DILISIC. Additionally, the stabilization of a complex system via DILISIC is addressed in a synthetic scenario: the consensus control of a team of flexible single-link arms. The dynamics of these agents are of fourth order, contain uncertainties, and are subject to external perturbations. The numerical results validate the applicability of the proposed method.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Institute of Electrical and Electronics Engineers
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
ARTIFICIAL NEURAL NETWORKS
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BIOLOGY ELEMENTS IN THE LOOP
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BRAIN-LIKE CONTROL DESIGN
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COMPUTATIONAL MODELING
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CONTROL SYSTEMS
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NONLINEAR DYNAMICAL SYSTEMS
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NONLINEAR MULTI-AGENT SYSTEMS (MASS)
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PERFORMANCE-GUARANTEED CONTROL
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PERTURBATION METHODS
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REAL-TIME SYSTEMS
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ROBUST CONTROL.
dc.subject
UNCERTAINTY
dc.subject.classification
Control Automático y Robótica
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Limbic System-Inspired Performance-Guaranteed Control for Nonlinear Multi-Agent Systems With Uncertainties
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-02-06T10:13:57Z
dc.identifier.eissn
2162-2388
dc.journal.pagination
1-12
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Rubio Scola, Ignacio Eduardo Jesus. Universidad Nacional de Rosario; Argentina
dc.description.fil
Fil: Garcia Carrillo, Luis Rodolfo. New Mexico State University.; Estados Unidos
dc.description.fil
Fil: Hespanha, Joao P.. University of California; Estados Unidos
dc.journal.title
IEEE Transactions on Neural Networks and Learning Systems
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1109/TNNLS.2021.3121232
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