Abstract
In this paper, the problem of flocking for Multi-Agent Systems (MAS) in presence of system uncertainties and unknown disturbances is investigated. A biologically-inspired novel distributed resilient controller based on a computational model of emotional learning in the mammalian brain is proposed. The methodology, known as Brain Emotional Learning Based Intelligent Controller (BELBIC), integrates a resilience mechanism with multi-objective properties into the distributed flocking control strategy. The developed strategy adopts the learning capabilities of BELBIC with the flocking that makes it a very promising approach, especially while dealing with system uncertainties and/or unknown disturbances. Furthermore, the low computational complexity of the designed method makes it very suitable for practical implementation in real-time applications. Eventually, the effectiveness of the developed intelligent resilient distributed flocking control approach is demonstrated through the several simulation scenarios.
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