The Development of Neural Network Based System Identification ...

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18 CHAPTER 2 LITERATURE REVIEW CATEGORY 1 FULL SCALED, HIGH ALTITUDE & LONG ENDURANCE UAS HELICOPTER · Total Weight = > 250 kg · Range = > 70 km · Service ceiling = > 3000 m · Endurance = > 6 hours Boeing A160 Hummingbird Northrop Grumman MQ-8 Fire Scout Boeing Unmanned Little Bird (ULB) CATEGORY 2 MEDIUM SCALED UAS HELICOPTER · Total Weight = 30 – 250 kg · Payload = > 10 kg · Range = 30 – 70 km · Service ceiling = 3000 m · Endurance = 3 – 6 hours Yamaha RMAX - BEAR: Berkeley Aerobot Team Rotomotion SR500 Schiebel Camcopter S-100 CATEGORY 3 SMALL SCALED UAS HELICOPTER · Total Weight = < 30 kg · Payload = 2 kg -10 kg · Range = < 10 km · Service ceiling = 3000 m · Endurance = 15 min – 1 hour Rotomotion SR 30 Bergen Industrial – BEAR Aerobot VARIO Benzin Trainer - CSIRO UAS CATEGORY 4 MINI UAS · Total Weight = < 10 kg · Payload = < 2 kg · Range = < 10 km · Service ceiling = < 300 m · Endurance = 5 min – 1 hour MIT Autonomous Indoor Quadrotor Draganflyer X6 Helicopter ArduCopter Hexa 3DR - Udrones CATEGORY 5 MICRO AERIAL VEHICLES (MAV) · Total Weight = < 1 kg · Payload = < 100 g · Range = < 1 km · Service ceiling = 250 m · Endurance = < 1 hour Epson MAV Skybotix Coax Micro Helicopter AirRobot MAV Figure 2.1 The categories of helicopter based UAS based on size, payload and flight performance. Generally, a guidance system uses information from the navigation blocks and mission goals to make appropriate decisions to generate trajectory reference for the low level controller. The automatic flight control system (AFCS) is a key autonomy-enabling functionality that increases the helicopter based UAS autonomy level from ‘level 0’ to ‘level 1’ on the autonomy level scale defined in Kendoul [2012]. In Level 0 (Remote Control), the control commands to the UAV are given by a remote external system or pilots, whereas in Level 1 (AFCS), the control commands to the unmanned vehicle are computed by the flight control system to control the helicopter’s position and orientation according to the given references. For the current project, the automatic flight control system (AFCS) is the main focus of our research since the AFCS is the first key autonomy
2.1 INTRODUCTION 19 Figure 2.2 The structure overview of guidance, navigation and control system for helicopter based UAS [Kendoul, 2012]. element that enables a UAS to be autonomous.
Page 1: The Development of Neural Network B
Page 5 and 6: ABSTRACT This thesis presents the d
Page 7: vii the MLP network, the prediction
Page 11: PUBLICATIONS The following is a lis
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Page 17 and 18: LIST OF FIGURES 1.1 Examples of typ
Page 19 and 20: LIST OF FIGURES xix 3.13 Overview o
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Page 29 and 30: NOMENCLATURE AFCS Automatic Flight
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68 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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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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