Intelligent control for DC-DC power converter with recurrent fuzzy neural network approach

Abstract

For many years, the control approaches for the dc-dc power converters are limited to PI controller structures. However, it gives the overshoot in output voltage as the rise time of response is reduced. To tackle this problem, an adaptive recurrent fuzzy neural network (ARFNN) control system is developed in this paper. The on-line adaptive laws of the ARFNN control scheme are derived based on the Lyapunov stability theorem, so that the stability of the system can be guaranteed. Experimental results show that the proposed ARFNN control scheme can achieve good regulation performances.