Meer over R Lozano

R Lozano

Unmanned Aerial Vehicles Embedded Control

Name: Unmanned Aerial Vehicles Embedded Control
Author: R Lozano

Embedded Control

Gebonden Engels 2010 9781848211278

205,52

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Samenvatting

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.

Specificaties

ISBN13:9781848211278

Taal:Engels

Bindwijze:gebonden

Aantal pagina's:344

Uitgever:John Wiley & Sons

Serie:ISTE

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Inhoudsopgave

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 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 (S ) 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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