Adaptive DC-Voltage control based on Type-2 neuro-fuzzy controller in a hybrid stand-alone power network with hydrogen fuel cell and battery

Abstract

Today, hydrogen fuel cells (HFCs) have become very popular in various applications because of their ability to be a clean energy source. One of the difficulties associated with HFCs is their sluggish response to variations in the load. This paper presents a nested control strategy based on a type-2 neuro-fuzzy controller (T2NFC) to improve the HFC's dynamic response in a hybrid stand-alone power network using HFC and battery. A system model is constructed using Matlab-Simulink. An interleaved converter is used to draw the maximal power from the HFC and reduce the ripple in the HFC's current. Two T2NFCs control DC voltage and battery charge/discharge current. The robustness of the T2NFC is evaluated for input disturbance, output disturbance, and both disturbances. The results show that the proposed control strategy is robust against input and output disturbances. Also, it provides improved dynamic response of the HFC, lower ripple in HFC current, and less overshoot or undershoot in DC voltage both in transient and steady-state. For step reference input, the proposed controller improves settling time of 24.06 % and overshoot of 59.55 % compared to the conventional PI controller. The results verify the effectiveness of the proposed controller under different operating conditions of hybrid stand-alone power network with fuel cell and battery.