Improving DC Power Supply Efficiency with Neural Network Controller
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Abstract
DC-DC converters can be found in almost every power electronics device. To improve the efficiency and controller response of a DC-DC converter to dynamical ~stem changes, neural network has been chosen as an alternative to classic methods. However, no prior work has been done in the neural network approach for control of a PSFB (phase-Shifted Full-Bridge) converter yet. In this research, a multi-layer feedforward neural network controller is proposed. The neural network based controller has the advantage of adaptive learning ability, and can work under the situation when the input voltage and load current fluctuate. Levenberg-Marquardt backpropagation training algorithm is used in computer simulation. The neural controller is then implemented on hardware using a DSP (digital signal processor). Satisfactory experimental results are obtained.
Suggested Citation
Weiming Li and Xiao-Hua Yu. "Improving DC Power Supply Efficiency with Neural Network Controller" IEEE International Conference Control and Automation.. May. 2007.
Available at: http://works.bepress.com/xhyu/9