Brain Emotional Learning Controller for Decision Making

Abstract

This project report presents to mitigate vibrations in structures during natural disasters, such as earthquakes, to protect buildings from structural damage and avoid loss of human lives. The closed loop system, is designed for this system, is inspired by the human brain. Brain Emotional Learning (BEL) algorithm is integrated with the PID controller. As BEL algorithm mimics the human brain learning process, it is implemented to adopt the PID controller gains in real time application where the BEL controller can be trained for real-time operations and set parameter for better performance and optimization. The BEL controller corrects the error signal and the corrected signal is known as the reward signal where BEL controller learns and adopts and upgrade the performance in the system. In this project, the BEL controller is used in conjunction with the PID controller to control the Magneto Rheological Damper to mitigate the vibrations in the structure. As MRD damper contains magnetorheological liquid as the carrier magnetic field is controlled by a command signal, which the generates the damping force to the structure. The PID and BEL-PID controllers are compared by performance, optimization, efficiency in mitigating the vibrations in the structure. The results shown are that the BEL-PID controller performance and its effectiveness in mitigating vibrations in the structure is better compared to PID controller. The significance of this project is to mitigate the vibrations in the structure by implanting intelligent controller in the system to reduce the earthquake’s losses and damage.