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Study on Wavelet Networks Applied in Buck Converters
Author: ChenBaoCi
Tutor: ShiJiYing
School: Tianjin University
Course: Theory and New
Keywords: Soft-switching Wavelet Network BUCK converter Network weights initialization The method of least squares
CLC: TM46
Type: Master's thesis
Year: 2005
Downloads: 134
Quote: 0
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Abstract
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This paper introduces the characteristics of nonlinear control system of the status quo and the soft-switching power converter; followed by application of a modular ideological analysis of the working process of the zero-current switching Buck Converter Buck converter zero current work using Laplace transform established state the exact discrete iterative mathematical model, reduced due to the difficulty of the additional resonant element to the equation of state of the system in different situations. Analyzed inverter steady state operating conditions, the simulation experiment, and the Buck converter obtained by the simulation waveform data using wavelet analysis tool to determine the difference between the stable operation and non-stable operation of the Buck converter for better control the application of wavelet network to provide theoretical guidance. Control advantages of wavelet network is that it combines neural network learning ability and by learning adaptive wavelet analysis of non-stationary random signal has a good local characteristics of the frequency domain and zoom capability, which makes the wavelet network has better approximation performance and approximation speed. The paper theoretically elaborated framework of wavelet network, the choice of the wavelet function, the initialization of the network parameters, the determination of the hidden layer nodes and parameter adjustment algorithm optimization of all aspects of the design, and integrated treatment based on the nonlinear parameters online adjusted to optimize control and other aspects of the problem. Finally, the simulation experiments, two different control models, a wavelet network control for Buck converter using fuzzy wavelet network control, and the other for the Buck ZCS-PWM converter. The wavelet network control with a new set of initial weights, application of organic combination of the Levenberg-Marquart algorithm and the method of least squares optimization algorithm for network parameter adjustment. Fuzzy wavelet network control the use of two-stage learning strategy, the use of Extended Kalman Filtering the algorithm adjustment nonlinear parameters, least-squares refinement ownership value. Finally, in MATLAB simulation, two control results and voltage feedback control for comparative analysis. This paper combines the advantage of the characteristics of the power converter and wavelet network control theory, wavelet theory is introduced into the field of soft-switching; application of wavelet analysis tool for the Buck converter stable operation with non-stable run waveform analysis; wavelet network control theory, and successfully design the control circuit model for simulation, optimization of the control parameters, and the intelligent control of the power system.
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CLC: > Industrial Technology > Electrotechnical > Transformers, converters and reactors > Converter
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