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Unmanned Aerial Vehicles: Embedded Control

Rogelio Lozano (Editor)
ISBN: 978-1-84821-127-8
352 pages
March 2010, Wiley-ISTE
Unmanned Aerial Vehicles: Embedded Control (1848211279) cover image
This book presents the basic tools required to obtain the dynamical models for aerial vehicles (in the Newtonian or Lagrangian approach). Several control laws are presented for mini-helicopters, quadrotors, mini-blimps, flapping-wing aerial vehicles, planes, etc. Finally, this book has two chapters devoted to embedded control systems and Kalman filters applied for aerial vehicles control and navigation. This book presents the state of the art in the area of UAVs. The aerodynamical models of different configurations are presented in detail as well as the control strategies which are validated in experimental platforms.
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Chapter 1. Aerodynamic Configurations and Dynamic Models 1
Pedro CASTILLO and Alejandro DZUL

1.1. Aerodynamic configurations 1

1.2. Dynamic models 6

1.2.1. Newton-Euler approach 7

1.2.2. Euler-Lagrange approach 9

1.2.3. Quaternion approach 10

1.2.4. Example: dynamic model of a quad-rotor rotorcraft 13

1.3. Bibliography 20

Chapter 2. Nested Saturation Control for Stabilizing the PVTOL Aircraft 21
Isabelle FANTONI and Amparo PALOMINO

2.1. Introduction 21

2.2. Bibliographical study 22

2.3. The PVTOL aircraft model 24

2.4. Control strategy 25

2.4.1. Control of the vertical displacement y 26

2.4.2. Control of the roll angle θ and the horizontal displacement x 27

2.5. Other control strategies for the stabilization of the PVTOL aircraft 33

2.6. Experimental results 33

2.7. Conclusions 38

2.8. Bibliography 38

Chapter 3. Two-Rotor VTOLMini UAV: Design, Modeling and Control 41
Juan ESCARENO, Sergio SALAZAR and Eduardo RONDON

3.1. Introduction 41

3.2. Dynamic model 43

3.2.1. Kinematics 44

3.2.2. Dynamics 44

3.2.3. Model for control analysis 48

3.3. Control strategy 48

3.3.1. Altitude control 49

3.3.2. Horizontal motion control 49

3.3.3. Attitude control 50

3.4. Experimental setup 51

3.4.1. Onboard flight system (OFS) 52

3.4.2. Outboard visual system 53

3.4.3. Experimental results 55

3.5. Concluding remarks 56

3.6. Bibliography 56

Chapter 4. Autonomous Hovering of a Two-Rotor UAV 59
Anand SANCHEZ, Juan ESCARENO and Octavio GARCIA

4.1. Introduction 59

4.2. Two-rotor UAV 60

4.2.1. Description 61

4.2.2. Dynamic model 61

4.3. Control algorithm design 67

4.4. Experimental platform 73

4.4.1. Real-time PC-control system (PCCS) 73

4.4.2. Experimental results 74

4.5. Conclusion 76

4.6. Bibliography 77

Chapter 5. Modeling and Control of a Convertible Plane UAV 79
Octavio GARCIA, Juan ESCARENO and Victor ROSAS

5.1. Introduction 79

5.2. Convertible plane UAV80

5.2.1. Vertical mode 80

5.2.2. Transition maneuver 81

5.2.3. Horizontal mode 81

5.3. Mathematical model 81

5.3.1. Translation of the vehicle 82

5.3.2. Orientation of the vehicle 83

5.3.3. Equations of motion 85

5.4. Controller design 86

5.4.1. Hover control 86

5.4.2. Transition maneuver control 96

5.4.3. Horizontal flight control 102

5.5. Embedded system 106

5.5.1. Experimental platform 106

5.5.2. Microcontroller 108

5.5.3. Inertial measurement unit (IMU) 109

5.5.4. Sensor fusion 109

5.6. Conclusions and future works 111

5.6.1. Conclusions 111

5.6.2. Future works 112

5.7. Bibliography 112

Chapter 6. Control of Different UAVs with Tilting Rotors 115
Juan ESCARENO, Anand SANCHEZ and Octavio GARCIA

6.1. Introduction 115

6.2. Dynamic model of a flying VTOL vehicle 116

6.2.1. Kinematics 117

6.2.2. Dynamics 118

6.3. Attitude control of a flying VTOL vehicle 119

6.4. Triple tilting rotor rotorcraft: Delta 119

6.4.1. Kinetics of Delta 120

6.4.2. Torques acting on the Delta 121

6.4.3. Experimental setup 123

6.4.4. Experimental results 125

6.5. Single tilting rotor rotorcraft: T-Plane 127

6.5.1. Forces and torques acting on the vehicle 127

6.5.2. Experimental results 129

6.6. Concluding remarks 131

6.7. Bibliography 132

Chapter 7. Improving Attitude Stabilization of a Quad-Rotor UsingMotor Current Feedback 133
Anand SANCHEZ, Luis GARCIA-CARRILLO, Eduardo RONDON and Octavio GARCIA

7.1. Introduction 133

7.2. Brushless DC motor and speed controller 134

7.3. Quad-rotor 138

7.3.1. Dynamic model 139

7.4. Control strategy 140

7.4.1. Attitude control 140

7.4.2. Armature current control 142

7.5. System configuration 144

7.5.1. Aerial vehicle 145

7.5.2. Ground station 146

7.5.3. Vision system 147

7.6. Experimental results 148

7.7. Concluding remarks 150

7.8. Bibliography 151

Chapter 8. Robust Control Design Techniques Applied toMini-Rotorcraft UAV: Simulation and Experimental Results 153
José Alfredo GUERRERO, Gerardo ROMERO, Rogelio LOZANO and Efraín ALCORTA

8.1. Introduction 153

8.2. Dynamic model 155

8.3. Problem statement 156

8.4. Robust control design 158

8.5. Simulation and experimental results 160

8.5.1. Simulations 160

8.5.2. Experimental platform 162

8.6. Conclusions 164

8.7. Bibliography 164

Chapter 9. Hover Stabilization of a Quad-Rotor Using a Single Camera 167
Hugo ROMERO and Sergio SALAZAR

9.1. Introduction 167

9.2. Visual servoing 168

9.2.1. Direct visual servoing 169

9.2.2. Indirect visual servoing 169

9.2.3. Position based visual servoing 170

9.2.4. Image-based visual servoing 171

9.2.5.Position-image visual servoing 172

9.3. Camera calibration 173

9.3.1. Two-plane calibration approach 173

9.3.2. Homogenous transformation approach 175

9.4. Pose estimation 177

9.4.1. Perspective of n-points approach 177

9.4.2. Plane-pose-based approach 179

9.5. Dynamic model and control strategy 181

9.6. Platform architecture 183

9.7. Experimental results 184

9.7.1. Camera calibration results 185

9.7.2. Testing phase 185

9.7.3. Real-time results 185

9.8. Discussion and conclusions 186

9.9. Bibliography 188

Chapter 10. Vision-Based Position Control of a Two-Rotor VTOL Mini UAV 191
Eduardo RONDON, Sergio SALAZAR, Juan ESCARENO and Rogelio LOZANO

10.1. Introduction 191

10.2. Position and velocity estimation 193

10.2.1. Inertial sensors 193

10.2.2. Visual sensors 193

10.2.3. Kalman-based sensor fusion 198

10.3. Dynamic model 200

10.4. Control strategy 203

10.4.1. Frontal subsystem (Scamy) 203

10.4.2. Lateral subsystem (Scamx) 204

10.4.3. Heading subsystem (Sψ) 204

10.5. Experimental test bed and results 204

10.5.1. Experimental results 206

10.6. Concluding remarks 207

10.7. Bibliography 207

Chapter 11. Optic Flow-Based Vision System for Autonomous 3D Localization and Control of Small Aerial Vehicles 209
Farid KENDOUL, Isabelle FANTONI and Kenzo NONAMI

11.1. Introduction 209

11.2. Related work and the proposed 3NKF framework 210

11.2.1. Optic flow computation 210

11.2.2.Structure from motion problem 212

11.2.3. Bioinspired vision-based aerial navigation 213

11.2.4. Brief description of the proposed framework 213

11.3. Prediction-based algorithm with adaptive patch for accurate and efficient opticflowcalculation 215

11.3.1. Search center prediction 215

11.3.2. Combined block-matching and differential algorithm 216

11.4. Optic flow interpretation for UAV 3D motion estimation and obstacles detection (SFMproblem) 219

11.4.1. Imaging model 219

11.4.2. Fusion of OF and angular rate data 220

11.4.3. EKF-based algorithm for motion and structure estimation 221

11.5. Aerial platform description and real-time implementation 223

11.5.1. Quadrotor-based aerial platform 223

11.5.2. Real-time software 225

11.6. 3D flight tests and experimental results 227

11.6.1. Experimental methodology and safety procedures 227

11.6.2. Optic flow-based velocity control 227

11.6.3. Optic flow-based position control 229

11.6.4. Fully autonomous indoor flight using optic flow 231

11.7. Conclusion and future work 233

11.8. Bibliography 234

Chapter 12. Real-Time Stabilization of an Eight-Rotor UAV Using Stereo Vision and Optical Flow 237
Hugo ROMERO, Sergio SALAZAR and José GÓMEZ

12.1. Stereo vision 238

12.2. 3D construction 242

12.3. Keypoints matching algorithm 245

12.4. Optical flow-based control 245

12.4.1. Lucas-Kanade approach 247

12.5. Eight-rotorUAV 249

12.5.1. Dynamic model 249

12.5.2. Control strategy 257

12.6. System concept 259

12.7. Real-time experiments 260

12.8. Bibliography 263

Chapter 13. Three-Dimensional Localization 265
Juan Gerardo CASTREJON-LOZANO and Alejandro DZUL

13.1. Kalman filters 266

13.1.1. Linear Kalman filter 266

13.1.2. Extended Kalman filter 269

13.1.3. Unscented Kalman filter 270

13.1.4. Spherical simplex sigma-point Kalman filters 278

13.2. Robot localization 285

13.2.1. Types of localization 285

13.2.2. Inertial navigation theoretical framework 286

13.3. Simulations 289

13.3.1.Quad-rotorhelicopter 289

13.3.2. Inertial navigation simulations 290

13.3.3. Conclusions 296

13.4. Bibliography 297

Chapter 14. Updated Flight Plan for an Autonomous Aircraft in a Windy Environment 301
Yasmina BESTAOUI and Fouzia LAKHLEF

14.1. Introduction 301

14.2. Modeling 304

14.2.1. Down-draftmodeling 304

14.2.2. Translational dynamics 305

14.3. Updated flight planning308

14.3.1. Basic problem statement 310

14.3.2. Hierarchical planning structure 311

14.4. Updates of the reference trajectories: time optimal problem 312

14.5. Analysis of the first set of solutionsS1 315

14.6. Conclusions 323

14.7. Bibliography 323

List of Authors 327

Index 331

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