Implementation of an Intelligent Adaptive Controller for an Electrohydraulic Servo System Based on a Brain Mechanism of Emotional Learning

In this paper, an experimental analysis of identification and an online intelligent adaptive position tracking control based on an emotional learning model of the human brain (BELBIC) for an electrohydraulic servo (EHS) system is presented. A mathematical model of the system is derived and the parameters of the model are identified. The BELBIC is designed based upon this dynamic model and utilized to control the real laboratorial EHS system. The experimental results are compared to those obtained from an optimal PID controller to prove that classic linear controllers fail to achieve good tracking of the desired output, especially when the hydraulic actuator operates at various frequencies and pressures. The results demonstrate an excellent improvement in control action, without any increase in control effort, for the proposed approach. Finally, it can be concluded from the experimental results that the BELBIC is able to respond quickly to any disturbance and variation in the system parameters, showing a high degree of adaptability and robustness due to its online learning ability.