Adjustable output voltage Zeta converter using neural network adaptive model reference control

Zeta converters are the fourth-order DC-DC converters capable of operating in both step-up and step-down modes and do not suffer from the polarity reversal problem. There are many applications which require a variable output voltage commanded by an external reference signal. So, the Zeta converters can be particularly useful for such applications. To achieve a Zeta converter with adjustable output voltage capable of following an external reference signal smoothly and accurately, there will be a need for a suitable control system. Since the Zeta converter model that is used in this paper is nonlinear, we propose a combination scheme of model reference adaptive control (MRAC) with neural networks (NN). In this paper, we propose and design a neural network adaptive model reference controller to control the output voltage of Zeta converter. Simulation results show the effectiveness of the proposed scheme for the Zeta converters with adjustable output voltage.