Improvement of energy efficiency and performance of an electrohydraulic actuator using brain emotional learning based intelligent controller (BELBIC)

In modern industries, to improve energy efficiency and performance, adaptive control applications are growing step by step owing to their ability to cope with the effect of nonlinearities and time-varying phenomena of the dynamic system in a stochastic environment. Electro-hydraulic actuators (EHA) are such a kind of dynamic system which can be easily affected by uncertainties. However, EHAs have a wide range of applications ranging from teleoperated excavation to precise numerical control. Meanwhile, various uncertain phenomena can easily influence the overall control performance. This paper presents a psycho-biological motivated adaptive control featured by an emotional learning mechanism: a brain emotional learning-based intelligent controller (BELBIC) to control the trajectory of the electrohydraulic actuator. The control signal generated by this computationally efficient controller consists of an adaptive control signal to compensate for the uncertainties and handle the nonlinearities. It tries to keep the trajectory error as minimum as possible, corresponding to a random disturbance. Experimental work was carried out to evaluate the performance compared to conventional PID and fuzzy-PID controllers. The results confirmed the effectiveness of the proposed BELBIC controller over the conventional PID and fuzzy PID controller. The proposed adaptive BELBIC controller provides an excellent response for a 0.5 Hz sinusoidal input signal where the PID and fuzzy PID show insufficient responses.