Paper Title:
Study on Genetic Neural Network Control Strategy for DC/DC Converter
  Abstract

A control method based on genetic neural network is presented to deal with the nonlinear object of the high-power PS-FB-ZVS PWM DC/DC converter. The control system optimizes the initial weight of the BP neural network and PID parameters tuning on line utilizing the genetic algorithm, which directly controls the object in closed-loop and has solved the problem that the controller network initial weight coefficient influences the control effect, thus, the optimal dynamic and steady state performance of the system is ensured. In the MATLAB environment, the control systems consisting of different controllers are simulated, and the output voltage and output current waveforms are obtained when the system is loaded by experiment. The results show that the controller has strong robustness, fast response speed, and small output voltage fluctuations with load changes.

  Info
Periodical
Advanced Materials Research (Volumes 268-270)
Edited by
Feng Xiong
Pages
1921-1927
DOI
10.4028/www.scientific.net/AMR.268-270.1921
Citation
X. X. Zhou, J. S. Li, D. Guo, "Study on Genetic Neural Network Control Strategy for DC/DC Converter", Advanced Materials Research, Vols. 268-270, pp. 1921-1927, 2011
Online since
July 2011
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Price
$32.00
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