The Development of Neural Network Based System Identification ...

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204 CHAPTER 7 FLIGHT CONTROL SYSTEM DESIGN: RESULTS AND DISCUSSION 5 Roll Angle (Degree) 0 −5 NNAPC−Offline Reference NNAPC−Online −10 0 50 100 150 200 250 300 350 400 Sample (k) Lateral Cyclic 1 0.5 0 −0.5 δ lat NNAPC−Offline δ lat NNAPC−Online Disturbance Pitch Angle (Degree) −1 0 50 100 150 200 250 300 350 400 Sample (k) 12 10 8 6 4 2 0 −2 (a) Roll angle, φ NNAPC−Offline Reference NNAPC−Online −4 0 50 100 150 200 250 300 350 400 Sample (k) Longitudinal Cyclic 0.4 0.2 0 −0.2 −0.4 −0.6 δ long NNAPC−Offline δ long NNAPC−Online Disturbance −0.8 0 50 100 150 200 250 300 350 400 Sample (k) (b) Pitch angle, θ Figure 7.14 The coupled roll-pitch NNAPC controllers’ response comparison under input disturbances. These disturbances are introduced one at a time with the control responses shown here being overlaps of two separate test runs.
7.3 EXPERIMENTAL RESULTS 205 Yaw Rate (deg/s) 80 60 40 20 0 −20 NNAPC−Offline Reference NNAPC−Online −40 0 50 100 150 200 250 300 350 400 Sample (k) Tail Rotor Collective Pitch 0.4 0.2 δ ped NNAPC−Offline δ ped NNAPC−Online Disturbance 0 −0.2 0 50 100 150 200 250 300 350 400 Sample (k) (a) Yaw rate, r 15 Altitude (cm) 10 5 NNAPC−Offline Reference NNAPC−Online 0 0 50 100 150 200 250 300 350 400 Sample (k) Collective Pitch 1 0.8 0.6 0.4 0.2 δ col NNAPC−Offline δ col NNAPC−Online 0 0 50 100 150 200 250 300 350 400 Sample (k) (b) Altitude, z Figure 7.15 The NNAPC controllers’ response comparison under input disturbances for yaw and altitude channels. These disturbances are introduced one at a time with the control responses shown here being overlaps of two separate test runs.
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The Development of Neural Network B
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ABSTRACT This thesis presents the d
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vii the MLP network, the prediction
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PUBLICATIONS The following is a lis
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xiv TABLE OF CONTENTS CHAPTER 4 CHA
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LIST OF FIGURES 1.1 Examples of typ
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LIST OF FIGURES xix 3.13 Overview o
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LIST OF FIGURES xxi 5.2 The predict
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LIST OF FIGURES xxiii 5.13 The pred
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LIST OF FIGURES xxv 7.1 The locatio
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LIST OF TABLES 3.1 The specificatio
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NOMENCLATURE AFCS Automatic Flight
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LIST OF TABLES xxxi NNARX QP RBF RC
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2 CHAPTER 1 INTRODUCTION Surveillan
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4 CHAPTER 1 INTRODUCTION is then de
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6 CHAPTER 1 INTRODUCTION the dynami
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8 CHAPTER 1 INTRODUCTION models [Sa
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10 CHAPTER 1 INTRODUCTION improved
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12 CHAPTER 1 INTRODUCTION Chapter 3
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Chapter 2 LITERATURE REVIEW The pur
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2.1 INTRODUCTION 17 • Inefficient
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2.1 INTRODUCTION 19 Figure 2.2 The
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2.2 HELICOPTER DYNAMICS MODELLING A
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2.3 NEURAL NETWORK BASED SYSTEM IDE
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2.4 AUTOMATIC FLIGHT CONTROL SYSTEM
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2.5 SUMMARY 53 design based on the
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56 CHAPTER 3 AERIAL PLATFORM AND CU
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Chapter 4 NEURAL NETWORK BASED SYST
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4.2 THE ARTIFICIAL NEURAL NETWORKS
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4.3 SYSTEM IDENTIFICATION WITH NEUR
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4.4 SUMMARY 117 Segment 1 Segment 2
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Chapter 5 NN BASED SYSTEM IDENTIFIC
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5.2 OFF-LINE BASED SYSTEM IDENTIFIC
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5.6 ON-LINE SYSTEM IDENTIFICATION 1
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5.6 ON-LINE SYSTEM IDENTIFICATION 1
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5.7 MODEL PERFORMANCE COMPARISON US
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5.8 SUMMARY 151 methods such as wei
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Page 217 and 218: 7.2 FLIGHT TESTS IMPLEMENTATION 185
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Page 225 and 226: 7.3 EXPERIMENTAL RESULTS 193 Flight
Page 227 and 228: 7.3 EXPERIMENTAL RESULTS 195 140 Ya
Page 229 and 230: 7.3 EXPERIMENTAL RESULTS 197 indica
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Page 233 and 234: 7.3 EXPERIMENTAL RESULTS 201 Yaw Ra
Page 235: 7.3 EXPERIMENTAL RESULTS 203 mainta
Page 239: 7.4 SUMMARY 207 data measured from
Page 242 and 243: 210 CHAPTER 8 CONCLUSIONS AND FUTUR
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Page 246 and 247: 214 REFERENCES B. W. Bequette. Non-
Page 248 and 249: 216 REFERENCES Konstantinos Dalamag
Page 250 and 251: 218 REFERENCES Wayne Johnson. Helic
Page 252 and 253: 220 REFERENCES B. Mettler, Mark B.
Page 254 and 255: 222 REFERENCES V. R. Puttige and S.
Page 256 and 257: 224 REFERENCES D.H. Shim. Hierarchi
Page 258 and 259: 226 REFERENCES Nikos Vitzilaios and
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