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Online Trained Simulation and
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大小:898 |
2010-07-05
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Abstract
A real time implementation aspect of backpropagation
learning framework for training of a feed-forward neural
network is proposed. The real time prototype of Back-
Propagation based Dynamic Neuro Controller (BDNC)
using DSP (TMS320LF2407A) is developed for buck
converter in order to eliminate the tuning of the PID
controller parameters. The detailed simulation process
through Simulink/Matlab is also given. It can be applied
to any linear or non-linear system. Software control of
BDNC provides flexible control of neural network
parameters like activation functions and learning rate.
Simulation results are in accordance with the practical
results.
A real time implementation aspect of backpropagation
learning framework for training of a feed-forward neural
network is proposed. The real time prototype of Back-
Propagation based Dynamic Neuro Controller (BDNC)
using DSP (TMS320LF2407A) is developed for buck
converter in order to eliminate the tuning of the PID
controller parameters. The detailed simulation process
through Simulink/Matlab is also given. It can be applied
to any linear or non-linear system. Software control of
BDNC provides flexible control of neural network
parameters like activation functions and learning rate.
Simulation results are in accordance with the practical
results.
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