Intelligent robust controller based on cognitive computing technologies. Pt. 1: cognitive control models with the brain emotional learning

In on-line control and decision-making systems, emotional brain training is a preferred methodology (compared to stochastic gradient-based and evolutionary algorithms) due to its low computational complexity and fast robust learning. To describe the emotional learning of the brain, a mathematical model was created - the brain emotional learning controller (BELC). The design of intelligent systems based on emotional signals based on control methods as soft computing technologies: artificial neural networks, fuzzy control and genetic algorithms. Based on the simulated mathematical model of mammals BEL, a controller architecture has been developed. Applied approach called “Brain Emotional Learning Based Intelligent Controller” (BELBIC) - a neurobiologically motivated intelligent controller based on a computational model of emotional learning in the mammalian limbic system. The article describes applied models of intelligent regulators based on emotional learning of the brain. BELBIC's learning capabilities; versatility and low computational complexity make it a very promising toolkit for on-line applications.