The Development of Neural Network Based System Identification ...

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58 CHAPTER 3 AERIAL PLATFORM AND CUSTOM-BUILT FLIGHT TEST SYSTEM Gyro Main Frames Main Drive Gear Tail Drive Gear Motor Battery Servo Brushless DC Motor 7 Channel Receiver Receiver/Servo Battery Bottom Bracket Landing Gear Mounting Points Figure 3.2 Side frame system and components attachment in TREX600 main structure. regarded as a secondary rotor attached to the shaft either below or above the main rotor position by an unrestrained teetering hinge. The stabiliser bar blade consists of two simple paddles which are attached to a rigid rod. The stabiliser bar receives the same cyclic pitch and roll inputs from the swash-plate but no collective input. The stabiliser mechanism introduces stability to the helicopter dynamics through the use of the gyroscopic effect of the stabiliser bar tip weights and the aerodynamic effect on the stabiliser bar paddles [Kim and Tilbury, 2004, Shim, 2000]. When the stabiliser bar rotates, the bar earns gyroscopic effect and it tends to remain in the same plane of rotation. This would make the helicopter momentarily maintain the current roll and pitch angle for a substantial time. Considering the helicopter model in Figure 3.3, in a hovering condition, the stabiliser bar angle β is known to be zero (level). If a wind gust or other disturbance knocks the helicopter out of its equilibrium state, the stabiliser bar will continue to rotate in the same inertial plane [Kim and Tilbury, 2004]. This would subsequently help the helicopter back to equilibrium state through stabiliser bar action on the cyclic angle of the main blade.
3.2 AIR VEHICLE DESCRIPTIONS 59 Main Rotor Rotation Plane Stabilizer Bar Rotation Plane Stabilizer Bar Teetering Hinge β Wind Gust Figure 3.3 The stabilising effect of the stabiliser bar. Figure adapted from Kim and Tilbury [2004]. The TREX600 class helicopter uses a standard Bell-Hiller actuation system to control the angle of the main rotor blade. In contrast to fixed wing aircraft propeller, the blade angle of a helicopter’s main rotor blade varies as it moves around the rotation plane in each cycle. The blade angle may be at a maximum at one point in its cycle around the mast and fall to a minimum value 180 ◦ later in the cycle. The main rotor blade angle is controlled through the action of the swash-plate. The swash-plate is a pair of plates, one rotating and the other fixed, positioned surrounding the rotor shaft that can be tilted in any direction by the control actuators as shown in Figure 3.4. Figure 3.4 shows two linkage arms coming from the swash-plate denoted as the Bell input and the Hiller input. The tilting motion of the swash-plate is accomplished by two cyclic actuators indicated as pitch servo input and roll servo input. The swash-plate is tilted fore and aft by the pitch servo input, and left and right by the roll servo input. The blade angle of the main rotor blades is manipulated by the combination of the Bell input from the swash-plate and the Hiller input from the stabiliser bar. The collective pitch input to the main rotor blade is achieved by lowering or raising the swash-plate. The washout arm with the slider prevents the collective input from affecting the stabiliser bar. The slider slides only when the collective input is applied and it remains stationary if only a cyclic input is applied. If the swash-plate is tilted forward, for example, the blade angle of the main rotor
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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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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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5.8 SUMMARY 153 would enable the im
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156 CHAPTER 6 NEURAL NETWORK BASED
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Chapter 7 FLIGHT CONTROL SYSTEM DES
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7.2 FLIGHT TESTS IMPLEMENTATION 185
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7.3 EXPERIMENTAL RESULTS 187 1 0.8
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7.3 EXPERIMENTAL RESULTS 189 Longit
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7.3 EXPERIMENTAL RESULTS 191 Pitch
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7.3 EXPERIMENTAL RESULTS 193 Flight
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7.3 EXPERIMENTAL RESULTS 195 140 Ya
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7.3 EXPERIMENTAL RESULTS 197 indica
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7.3 EXPERIMENTAL RESULTS 199 20 100
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7.3 EXPERIMENTAL RESULTS 201 Yaw Ra
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7.3 EXPERIMENTAL RESULTS 203 mainta
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7.3 EXPERIMENTAL RESULTS 205 Yaw Ra
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7.4 SUMMARY 207 data measured from
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210 CHAPTER 8 CONCLUSIONS AND FUTUR
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212 CHAPTER 8 CONCLUSIONS AND FUTUR
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214 REFERENCES B. W. Bequette. Non-
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216 REFERENCES Konstantinos Dalamag
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218 REFERENCES Wayne Johnson. Helic
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220 REFERENCES B. Mettler, Mark B.
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222 REFERENCES V. R. Puttige and S.
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224 REFERENCES D.H. Shim. Hierarchi
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226 REFERENCES Nikos Vitzilaios and
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