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

机译:基于大脑情感学习的智能控制器的实现,用于植入多功能系统

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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.
机译:基于大脑情感学习的智能控制器(BELBIC)是一种基于哺乳动物林系统情感学习的计算模型的神经能源动机。 Belbic的学习能力,多目标属性和低计算复杂性使其成为实时应用中实现的非常有前途的工具。我们的研究以原始的方式与植物控制策略的贝尔贝里奇方法相结合,以便执行多个无人机系统(UAS)的实时协调。在这种情况下,Belbic的特点良好,由于自主代理的几乎总是完全知道的,因此,由于它们在靠近近距离操作,因此它们受到侵略性的外部干扰。基于多个四旋翼型UAS平台的协调的数值和实验结果证明了该方法的适用性和令人满意的性能。

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