Implementation of Brain Emotional Learning-Based Intelligent Controller for Flocking of Multi-Agent Systems

The 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 BELBI...

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Bibliographic Details
Published in:IFAC-PapersOnLine 2017-07, Vol.50 (1), p.6934-6939
Main Authors: Jafari, Mohammad, Fehr, Ric, Carrillo, Luis Rodolfo Garcia, Quesada, Eduardo Steed Espinoza, Xu, Hao
Format: Article
Language:English
Subjects:
adaptive neural
applications
embedded computer control systems
fuzzy control
knowledge based control
Reinforcement learning control
tele-robot
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Summary:The 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.
ISSN:2405-8963
2405-8963
DOI:10.1016/j.ifacol.2017.08.1219