شماره ركورد كنفرانس :
3222
عنوان مقاله :
Adjustable Output Voltage Zeta Converter Using Neural Network Adaptive Model Reference Control
پديدآورندگان :
Moaveni B Iran University of Science and Technology , Abdollahzadeh H Iran University of Science and Technology , Mazoochi M Islamic Azad University East-Tehran Branch
كليدواژه :
Zeta Converter , Neural Network , Model Reference Adaptive Control
عنوان كنفرانس :
دومين كنفرانس بين المللي كنترل، ابزار دقيق و اتوماسيون
چكيده لاتين :
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. In the other hand, there are many applications which require a variable output voltage commanded by an external reference signal. So, the Zeta converters with the adjustable output voltage can be useful in many applications. To achieve a Zeta converter with the adjustable output voltage which can follow an external reference signal smoothly and accurately, there is needed to use 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.