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Transactions: WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
Transactions ID Number: 52-524
Full Name: Chun-Fei Hsu
Position: Associate Professor
Age: ON
Sex: Male
Address: Department of Electrical Engineering, Chung Hua University, Hsin-Chu 300, Taiwan
Country: TAIWAN
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E-mail address: fei@chu.edu.tw
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Title of the Paper: Adaptive wavelet neural controller design for a DC-DC power converter using FPGA
Authors as they appear in the Paper: Chun-Fei Hsu and Yu-Hsiung Lin
Email addresses of all the authors: fei@chu.edu.tw, bear@chu.edu.tw
Number of paper pages: 26
Abstract: The DC-DC power converters are widely used; however, the controller of the DC-DC power converters cannot easily design if the load dynamics vary widely. The main advantage of the wavelet neural network (WNN) is its fast learning rate compared to other neural networks; thus this paper proposes an adaptive wavelet neural control (AWNC) system for a forward DC-DC power converter. The proposed AWNC system is composed of a neural controller and a robust controller. The neural controller uses a WNN to online mimic an ideal controller, and the robust controller is designed to cope with the approximation error between the neural controller and the ideal controller. A proportional-integral (PI)-type parameter tuning mechanism is derived based on the Lyapunov stability theory; thus not only the system stability can be achieved but also the convergence of the tracking error can be speeded up. Finally, a field-programmable gate array (FPGA) chip is adopted to implement the pro!
posed AWNC scheme for possible low-cost and high-performance industrial applications. The experimental results show the forward DC-DC power converter can convert a certain electrical voltage to another level of electrical voltage even under the input voltage and load resistance variations using the proposed AWNC system.
Keywords: adaptive control; robust control; wavelet neural network; DC-DC power converter; FPGA implementation.
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