A biologically-inspired distributed resilient flocking control for multi-agent system with uncertain dynamics and unknown disturbances

In this paper, the problem of flocking of MultiAgent 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 mammalian brain is proposed. The methodology, known as Brain Emotional Learning Based Intelligent Controller (BELBIC), embeds a resilience mechanism with multi-objective properties into the flocking control strategy in a distributed fashion. The new strategy combines the learning capabilities of BELBIC with the flocking, and makes it a very promising approach, especially while dealing with system uncertainties and/or unknown disturbances. In addition, the low computational complexity of the proposed method makes it very suitable for practical implementation in real-time applications. Eventually, the effectiveness of the proposed intelligent resilient flocking control approach is demonstrated for flocking control of MAS.