The Development of Neural Network Based System Identification ...

xxii
LIST OF FIGURES
5.7 The prediction from MLP network model for roll dynamics. (a) The
one-step ahead prediction and measurement data plot. (b) The error plot
between one-step ahead prediction and the measurement data. The red
dashed line indicates estimation from the neural network model while
the solid blue line with ‘x’ marker represents the output measurement. 129
5.8 The prediction from MLP network model for pitch dynamics. (a) The
one-step ahead prediction and measurement data plot. (b) The error plot
between one-step ahead prediction and the measurement data. The red
dashed line indicates estimation from the neural network model while
the solid blue line with ‘x’ marker represents the output measurement. 129
5.9 The 5 steps ahead prediction of MLP network model for (a) Pitch
dynamics; and (b) Roll dynamics. The solid blue line with ‘x’ marker is
the measured output while the red dashed line indicates the prediction
from neural network model. 130
5.10 The percentage of Root Mean Square Error (RMSE) of the HMLP
network trained with different network structures and number of hidden
neurons.
The neural network training was carried out using off-line
Levenberg-Marquardt (LM) algorithm. 134
5.11 The percentage of Root Mean Square Error (RMSE) comparison for
different hidden neurons selection. The k-cross validation process was
conducted for HMLP network with network structure of 6 regressors
(n y = 2 and n u = 1). The neural network training was carried out using
off-line Levenberg-Marquardt (LM) algorithm. 135
5.12 The prediction from the HMLP network for roll dynamics. (a) The onestep
ahead prediction overlaid with the measured helicopter responses. (b)
The error plot between one-step ahead prediction and the measurement
data. The red dashed line indicates estimation from the HMLP neural
network model while solid blue line with ‘x’ marker represents the output
measurement. 136