Page 322 - Neural Network Modeling and Identification of Dynamical Systems

INDEX 313
ANN, 144 control system, 160 Outputs, 39, 41, 42, 48–50, 59, 66,
neural network, 203 learning, 51, 203 93–99, 101, 106–108, 117,
process, 4, 69, 77, 132, 140, 144 motion model, 111 131, 132, 140, 144
rate, 53 NARX model, 132 ANN, 108
reinforcement, 51, 52 outputs, 58 network, 45, 46, 60, 64
strategy, 211 stabilizer actuator, 109 neural network, 58
supervised, 51, 52, 132 supervised learning, 52 neurons, 50
unsupervised, 51 training, 57, 58, 62 target, 107
Linear ANN model, 43 Neurocontroller true, 58, 63
configuration, 144
M ensemble, 120 P
Maneuverable aircraft, 5, 6, 78, mutually agreed, 120 Parametric adaptation, 22
134, 139, 200, 208, 210, mutually coordinated, 124 Partial derivatives, 61, 62, 200, 208
216, 217, 219, 225 synthesis, 5, 114, 141, 156 Partial differential equations
Manned aircraft, 1, 2 Neurocorrector, 118, 125 (PDE), 3, 28, 165
Model predictive control (MPC), Neurons Phase angles, 85, 87
5, 139, 154, 156, 157 inputs, 45, 50 Pitch, 18, 105, 106, 108, 134, 158,
Model reference adaptive control outputs, 50 200, 201, 208–210, 217
(MRAC), 5, 27, 139 Nonlinear angle, 18, 77, 78, 105, 134, 201,
Motion controlled systems, 100 209, 217
aircraft, 4, 5, 72, 101–103, 108, dynamical systems, 4, 5 angular velocity, 76, 78
117, 131, 133, 135, 139, dynamical systems control, 101, channel, 208
152, 154, 158, 168, 199, 139 moment, 105, 152, 200, 216–218
200, 208 ODEs, 217 moment coefficient, 18, 134, 201
model, 108, 109, 118, 134, 153, Pitching
199 O moment coefficient, 78
plant, 103 Object Pitching moment, 77
MRAC system, 145, 150, 151, 154, adaptation, 22 Plant, 75, 93, 102–104, 106, 108,
116, 125
157–159, 161 control, 24, 106
Multilayer neural network, 5, 131, model, 154 model, 107, 108
134, 156 moving, 16 motion, 103
Multimode dynamical system Onboard control systems, 94 state space, 103
(MDS), 5, 117 Online adaptation, 63, 192 Polyharmonic control signal, 212
Prediction error, 63, 67, 97,
Operation 175–178
N modes, 72, 95, 116, 118, 120, 123
NARX model, 132, 133, 176, 206 network, 42, 52 R
neural network, 132 Optimal Recurrent neural network
Network control law, 121 architectures, 172
controller, 140 control problem, 193 Recurrent neural network
inputs, 43, 45, 60–62 synthesis, 5 training, 65, 189
operation, 42, 52 tracking control problem, 135 Recurrent neural networks (RNN),
outputs, 45, 46, 60, 64 Optimality criterion, 118, 120–124, 43, 47, 65, 66, 97, 99, 101,
outputs derivatives, 61, 66 126, 193 170, 172, 173, 187, 192
Network models (NM), 38 Ordinary differential equations Reference model (RM), 25
Neural controllers, 5, 102, 110, 112, (ODEs), 3, 4, 19, 28, 29, Roll angle, 18
119, 120, 124, 125, 144 165, 168–170, 172, 177, Rotational motion, 221
Neural network 180–183, 191, 199, 200,
black box, 4, 94 209 S
control, 103, 110 nonlinear, 217 Semiempirical