The Development of Neural Network Based System Identification ...

LIST OF FIGURES
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7.1 The location of poles of the extracted linear models from the instantaneous
linearisation process. The poles were obtained at every simulation interval
and are super-positions in the z-domain plot. 187
7.2 The control response comparison with N p = 10 and different r w values for
the roll and pitch channels. The dash-dotted lines indicate the constraint
limits imposed on the control input calculation. 189
7.3 The NNAPC response comparison with r w = 1.5 and various N p values
for roll and pitch channels. 191
7.4 The NNAPC response comparison with r w = 1.5 and various N p values
for the yaw channel. 192
7.5 The block diagram showing the links between the on-board flight controller,
the bare yaw dynamic and the components of augmented system
in the yaw channel: the yaw rate gyro and the PI controller. G T indicates
the actuator gain for the actuator that controls the tail rotor pitch while
K ψ denotes the controller gain for yaw angle compensation. 193
7.6 The NNAPC response comparison with various K ψ values for the yaw
angle compensation. The prediction horizon N p = 10 and control penalty
factor r w = 1.5 are selected for this controller with constraints on control
input rate −0.015 ≤ ∆u(k) ≤ 0.015. 195
7.7 The 4 DOF NNAPC controller with recursive NN training in action. 196
7.8 The control responses of the 4 DOF NNAPC controller with recursive
NN training during hovering flight test. 197
7.9 The corresponding control signals from the 4 DOF NNAPC controller
with recursive NN training during hovering flight test. 198
7.10 The parameter variation in collective pitch setting. (a) The original
collective pitch and throttle setting from the RC transmitter which was
used in the off-line NN training phase. (b) The new collective and throttle
setting for controller comparison test under parameter variation. 199