Abstract
A neural network controller for DC/DC buck converters is proposed, and then the hardware implementation problem of the controller based on FPGA is discussed in this paper. The neural network is trained using bp method. The reconfigurable feature is analyzed and then three basic reconfigurable units are built based on SG / Simulink. The simulation results show that the FPGA-based reconfigurable neural network controller can not only achieve good performances but effectively save resources.
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© 2009 Springer-Verlag Berlin Heidelberg
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Shen, Y., Li, T., Ji, Z. (2009). Research on the Reconfigurable Implementation of Neural Network Controller Based on FPGA for DC-DC Converters. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_131
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DOI: https://doi.org/10.1007/978-3-642-01510-6_131
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01509-0
Online ISBN: 978-3-642-01510-6
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