Implementation of brain emotional learning-based intelligent controller for flocking of multi-agent systems

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dc.contributor.authorJafari, Mohammad
dc.contributor.authorFehr, Ric
dc.contributor.authorGarcia Carrillo, Luis Rodolfo
dc.contributor.authorEspinoza Quesada, Eduardo Steed
dc.date.accessioned2022-02-24T21:59:33Z
dc.date.available2022-02-24T21:59:33Z
dc.date.issued2017-07
dc.description.abstractThe Brain Emotional Learning Based Intelligent Controller (BELBIC) is a neurobiologically-motivated intelligent controller based on a computational model of emotional learning in mammalian limbic system. The learning capabilities, multi-objective properties, and low computational complexity of BELBIC make it a very promising tool for implementation in real-time applications. Our research combines, in an original way, the BELBIC methodology with a flocking control strategy, in order to perform real-time coordination of multiple Unmanned Aircraft Systems (UAS). The characteristics of BELBIC fit well in this scenario, since almost always the dynamics of the autonomous agents are not fully known, and furthermore, since they operate in close proximity, they are subjected to aggressive external disturbances. Numerical and experimental results based on the coordination of multiple quad rotorcraft UAS platforms demonstrate the applicability and satisfactory performance of the proposed method.en_US
dc.description.abstractThe Brain Emotional Learning Based Intelligent Controller (BELBIC) is a neurobiologically-motivated intelligent controller based on a computational model of emotional learning in mammalian limbic system. The learning capabilities, multi-objective properties, and low computational complexity of BELBIC make it a very promising tool for implementation in real-time applications. Our research combines, in an original way, the BELBIC methodology with a flocking control strategy, in order to perform real-time coordination of multiple Unmanned Aircraft Systems (UAS). The characteristics of BELBIC fit well in this scenario, since almost always the dynamics of the autonomous agents are not fully known, and furthermore, since they operate in close proximity, they are subjected to aggressive external disturbances. Numerical and experimental results based on the coordination of multiple quad rotorcraft UAS platforms demonstrate the applicability and satisfactory performance of the proposed method.
dc.identifier.citationJafari, M., Xu, H. and Carrillo, L.R.G., 2017, May. Brain emotional learning-based intelligent controller for flocking of multi-agent systems. In 2017 American Control Conference (ACC) (pp. 1996-2001). IEEE.en_US
dc.identifier.citationJafari, M., Xu, H. and Carrillo, L.R.G., 2017, May. Brain emotional learning-based intelligent controller for flocking of multi-agent systems. In 2017 American Control Conference (ACC) (pp. 1996-2001). IEEE.
dc.identifier.doihttps://doi.org/10.1016/j.ifacol.2017.08.1219
dc.identifier.urihttps://hdl.handle.net/1969.6/90202
dc.language.isoen_USen_US
dc.language.isoen_US
dc.publisherElsevieren_US
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectreinforcement learning controlen_US
dc.subjectadaptive neuralen_US
dc.subjectfuzzy controlen_US
dc.subjectembedded computer control systemsen_US
dc.subjectapplicationsen_US
dc.subjectknowledge based controlen_US
dc.subjectreinforcement learning control
dc.subjectadaptive neural
dc.subjectfuzzy control
dc.subjectembedded computer control systems
dc.subjectapplications
dc.subjectknowledge based control
dc.titleImplementation of brain emotional learning-based intelligent controller for flocking of multi-agent systemsen_US
dc.titleImplementation of brain emotional learning-based intelligent controller for flocking of multi-agent systems
dc.typeArticleen_US
dc.typeArticle

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