Design of FPGA Based Neural Network Controller for Earth Station Power System
Abstract: Automation of
generating hardware description language code of neural networks models can
highly decrease time of implementation those networks into a digital devices,
thus significant money savings. To implement the neural network into hardware
design, it is required to translate generated model into device structure. VHDL
language is used to describe those networks into hardware. VHDL code has been
proposed to implement ANNs as well as to present simulation results with
floating point arithmetic of the earth station and the satellite power systems
using ModelSim® PE 6.6 simulator tool. Integration between MATLAB® and VHDL is
used to save execution time of computation. The results shows that a good
agreement between MATLAB and VHDL and a fast and flexible feed forward NN which
is capable of dealing with floating point arithmetic operations; minimum number
of CLB slices; and good speed of performance. FPGA synthesis results are
obtained with view RTL schematic and technology schematic from Xilinix tool.
Minimum number of utilized resources is obtained by using Xilinix VERTIX5.
Author: Hanaa T. El-Madany,
Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah
Journal Code: jptkomputergg120050
