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E-raamat: Indoor Navigation Strategies for Aerial Autonomous Systems

(Engineer in research and development in a Start-Up in France), (Assistant Professor of Automatic Control, Tec), (Researcher, French National Research Foundation (CNRS), Laboratory Heudiasyc,University of Technology of Compiegne, France)
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 10-Nov-2016
  • Kirjastus: Butterworth-Heinemann Inc
  • Keel: eng
  • ISBN-13: 9780128053393
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Indoor Navigation Strategies for Aerial Autonomous SystemsSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 10-Nov-2016
  • Kirjastus: Butterworth-Heinemann Inc
  • Keel: eng
  • ISBN-13: 9780128053393
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Indoor Navigation Strategies for Aerial Autonomous Systems presents the necessary and sufficient theoretical basis for those interested in working in unmanned aerial vehicles, providing three different approaches to mathematically represent the dynamics of an aerial vehicle.

The book contains detailed information on fusion inertial measurements for orientation stabilization and its validation in flight tests, also proposing substantial theoretical and practical validation for improving the dropped or noised signals. In addition, the book contains different strategies to control and navigate aerial systems.

The comprehensive information will be of interest to both researchers and practitioners working in automatic control, mechatronics, robotics, and UAVs, helping them improve research and motivating them to build a test-bed for future projects.

  • Provides substantial information on nonlinear control approaches and their validation in flight tests
  • Details in observer-delay schemes that can be applied in real-time
  • Teaches how an IMU is built and how they can improve the performance of their system when applying observers or predictors
  • Improves prototypes with tactics for proposed nonlinear schemes

Muu info

Presents the necessary and sufficient theoretical basis for those interested in working in unmanned aerial vehicles, providing three different approaches
About the Authors ix
Preface xi
Acknowledgments xiii
Part 1 Background
1 State-of-the-Art
3(28)
1.1 Mathematical Representation of the Vehicle Dynamics
4(2)
1.2 Attitude Estimation Using Inertial Sensors
6(1)
1.3 Delay Systems & Predictors
7(1)
1.4 Data Fusion for UAV Localization
8(3)
1.5 Control & Navigation Algorithms
11(4)
1.6 Trajectory Generation & Tracking
15(1)
1.7 Obstacle Avoidance
16(4)
1.8 Teleoperation
20(11)
References
22(9)
2 Modeling Approaches
31(22)
2.1 Force and Moment in a Rotor
31(1)
2.2 Euler--Lagrange Approach
32(5)
2.3 Newton--Euler Approach
37(3)
2.4 Quaternion Approach
40(9)
2.5 Discussion
49(4)
References
50(3)
Part 2 Improving Sensor Signals for Control Purposes
3 Inertial Sensors Data Fusion for Orientation Estimation
53(22)
3.1 Attitude Representation
53(2)
3.2 Sensor Characterization
55(1)
3.3 Attitude Estimation Algorithms
56(8)
3.4 A Computationally-Efficient Kalman Filter
64(9)
3.5 Discussion
73(2)
References
74(1)
4 Delay Signals & Predictors
75(34)
4.1 Observer--Predictor Algorithm for Compensation of Measurement Delays
76(11)
4.2 State Predictor--Control Scheme
87(18)
4.3 Discussion
105(4)
References
107(2)
5 Data Fusion for UAV Localization
109(24)
5.1 Sensor Data Fusion
109(7)
5.2 Prototype and Numerical Implementation
116(2)
5.3 Flight Tests and Experimental Results
118(6)
5.4 OptiTrack Measurements vs EKF Estimation
124(2)
5.5 Rotational Optical Flow Compensation
126(2)
5.6 Discussion
128(5)
References
128(5)
Part 3 Navigation Schemes & Control Strategies
6 Nonlinear Control Algorithms with Integral Action
133(24)
6.1 From PD to PID Controllers
133(3)
6.2 Saturated Controllers with Integral Component
136(9)
6.3 Integral and Adaptive Backstepping Control -- IAB
145(8)
6.4 Discussion
153(4)
References
154(3)
7 Sliding Mode Control
157(24)
7.1 From the Nonlinear Attitude Representation to Linear MIMO Expression
157(3)
7.2 Nonlinear Optimal Controller with Integral Sliding Mode Design
160(6)
7.3 Numerical Validation
166(8)
7.4 Real-Time Validation
174(4)
7.5 Discussion
178(3)
References
178(3)
8 Robust Simple Controllers
181(32)
8.1 Nonlinear Robust Algorithms Based on Saturation Functions
182(14)
8.2 Robust Control Based on an Uncertainty Estimator
196(15)
8.3 Discussion
211(2)
References
212(1)
9 Trajectory Generation, Planning & Tracking
213(30)
9.1 Quadrotor Mathematical Description
214(3)
9.2 Time-Optimal Trajectory Generation
217(3)
9.3 UAV Routing Problem for Inspection-Like Missions
220(3)
9.4 Trajectory Tracking Problem
223(1)
9.5 Simulation Results
224(16)
9.6 Discussion
240(3)
References
241(2)
10 Obstacle Avoidance
243(20)
10.1 Artificial Potential Field Method
243(5)
10.2 Obstacle Avoidance Algorithm
248(9)
10.3 Limit-Cycle Obstacle Avoidance
257(4)
10.4 Discussion
261(2)
References
261(2)
11 Haptic Teleoperation
263(14)
11.1 Experimental Setup
264(5)
11.2 Collision Avoidance
269(1)
11.3 Haptic Teleoperation
270(1)
11.4 Real-Time Experiments
271(3)
11.5 Discussion
274(3)
References
275(2)
Index 277
He received the best Ph.D. thesis of Automatic Control award from club EEA, (France) in 2005. His research topics cover: real-time control applications, non-linear dynamics and control, aerospace vehicles, vision and underactuated mechanical systems. She obtained her B.S degree in Electronics and Telecommunications Engineering in 2005 and her M.Sc degree in Automation and Control in 2007 from the Hidalgo State University, Mexico. In 2009 she obtained her Ph.D. degree in Automatic Control from the University of Technology of Compiègne, France. He has been visiting researcher at the Lund Institute of Technology, Lund, Sweden (in 2006), Université de Technologie de Compiegne, Compiegne, France (in 2007), University of Florianopolis, Brazil (in 2010), and at the University of Sheffield (UK) (in 2014). He has co-authored more than 15 papers in middle or top impact journals. His research interests are within the broad area of time delay systems, embedded control systems and control of autonomous vehicles.
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