Flight Formation Control

José Alfredo Guerrero joined the Department of Electronic Engineering at the University Autonomous of Tamaulipas (UAT), Mexico in 2000 where he worked until 2006. His research interests are in the analysis and synthesis of multi-agent coordination control and nonlinear control with applications to Unmanned Aerial Vehicles, Autonomous Underwater Vehicles and robust and optimal control.Rogelio Lozano, after holding various positions, including visiting positions at the University of Newcastle in Australia, NASA Langley Research Center, VA, and LAG in France, has been the head of the UMI 3175 LAFMIA at CINVESTAV Mexico since April 2008. He has been a CNRS Research Director since 1990 and acted as Associate Editor for Automatica and Int. J. of Adaptive Control and Signal Processing.

“Overall this book delivers necessary backgrounds, basic and advanced nonlinear control algorithms and the associated challenges such as visual navigation and communication for those who are interested in studying and developing UAV formation flight strategies with guaranteed stability and performance.”  (The Aeronautical Journal, 3 February 2015)

• Chapter 1. Introduction 1J.A. GUERRERO1.1. Motivation 11.2. Historical background 41.3. Flight control 91.4. Flight formation control 111.5. Outline of the book 131.6. Bibliography 15Chapter 2. Theoretical Preliminaries 19J.A. GUERRERO2.1. Passivity 192.2. Graph theory 202.3. Robustness problems 212.4. Bibliography 25Chapter 3. Multiagent Coordination Strategies 27J.A. GUERRERO, R. LOZANO, M.W. SPONG, N. CHOPRA3.1. Introduction 283.2. Controllability and observability of interconnections 283.3. Formation leader tracking 373.4. Time-varying trajectory tracking 403.5. Linear high-order multiagent consensus 443.6. Conclusion 493.7. Bibliography 50Chapter 4. Robust Control Design of Multiagent Systems with Parametric Uncertainty 51J.A. GUERRERO, G. ROMERO4.1. Introduction 524.2. Robust control design 544.3. Robust stability analysis 564.4. Robust stability of time-delay systems 614.5. Application to multiagent systems 624.6. Conclusions 734.7. Bibliography 73Chapter 5. On Adaptive and Robust Controlled Synchronization of Networked Robotic Systems on Strongly Connected Graphs 75Y.-C. LIU, N. CHOPRA5.1. Summary 755.2. Introduction 755.3. Problem formulation 775.4. Adaptive controlled synchronization on strongly connected graphs 795.5. Robust controlled synchronization on strongly connected graph 835.6. Numerical examples 875.7. Conclusions 935.8. Appendix 945.9. Bibliography 95Chapter 6. Modeling and Control of Mini UAV 99G. FLORES COLUNGA, J.A. GUERRERO, J. ESCAREÑO, R. LOZANO6.1. Introduction 996.2. General model 1016.3. Control of a mini tailsitter 1036.4. Quad-tilting rotor convertible MAV 1176.5. Concluding remarks 1316.6. Bibliography 132Chapter 7. Flight Formation Control Strategies for Mini UAVs 135J.A. GUERRERO7.1. Introduction 1357.2. Formation geometry 1377.3. Communication network 1387.4. Dynamic model 1397.5. Formation flying control based on coordination 1427.6. Formation flying control based on nested saturations 1487.7. Trajectory-tracking control 1537.8. Simulation results 1587.9. Conclusions 1627.10. Bibliography 162Chapter 8. Formation Based on Potential Functions 165L. GARCÍA, A. DZUL8.1. Introduction 1658.2. Dynamical model 1668.3. Formation control 1678.4. Position control 1708.5. Simulation results 1838.6. Conclusions 1898.7. Bibliography 189Chapter 9. Quadrotor Vision-Based Control 191J.E. GOMEZ-BALDERAS, J.A. GUERRERO, S. SALAZAR, R. LOZANO, P. CASTILLO9.1. Introduction 1919.2. Quadrotor dynamic model and control 1949.3. Computer vision preliminaries 1979.4. Tracking of a visual target 2019.5. Tracking of a visual line 2099.6. Embedded architecture 2149.7. Experimental results 2149.8. Conclusions 2219.9. Bibliography 221Chapter 10. Toward Vision-Based Coordination of Quadrotor Platoons 225L.R. GARCÍA CARRILLO, J.A. GUERRERO, R. LOZANO10.1. Introduction 22510.2. Problem statement 22710.3. Dynamic model and control of a quadrotor 22810.4. Vision-based position estimation 22910.5. Coordination position control of two quadrotors 23510.6. Architecture of the experimental platforms 23710.7. Experimental results 24010.8. Conclusions and future work 24210.9. Bibliography 243Chapter 11. Optimal Guidance for Rotorcraft Platoon Formation Flying in Wind Fields 247J.A. GUERRERO, Y. BESTAOUI, R. LOZANO11.1. Introduction 24711.2. Preliminaries 25011.3. Path planning 25111.4. Quadrotor formation control scheme 25811.5. Quadrotor trajectory-tracking control 25811.6. Simulation results 25911.7. Conclusions and future work 26411.8. Bibliography 264Chapter 12. Impact of Wireless Medium Access Protocol on the Quadrotor Formation Control 267J.A. GUERRERO, Y. CHALLAL, P. CASTILLO12.1. Introduction 26712.2. Multiquadrotor consensus 26912.3. Multiagent consensus over wireless networks 27212.4. Quadrotor consensus over wireless networks 27512.5. Simulation results 27812.6. Conclusions and future work 28212.7. Bibliography 282Chapter 13. MAC Protocol for Wireless Communications 285A. MENDEZ, M. PANDURO, O. ELIZARRARAS, D. COVARRUBIAS13.1. Introduction 28513.2. Protocols of medium access control 28713.3. Proposed MAC protocol 29613.4. Experimental setup and results 29913.5. Conclusions 30013.6. Acknowledgments 30113.7. Bibliography 301Chapter 14. Optimization of a Scannable Pattern for Bidimensional Antenna Arrays to Provide Maximum Performance 305A. REYNA, M.A. PANDURO, A. MENDEZ14.1. Introduction 30514.2. Design of planar antenna arrays 30614.3. Design of concentric ring arrays 31414.4. Discussions and open problems 31914.5. Conclusions 32014.6. Acknowledgments 32014.7. Bibliography 320List of Authors 323Index 325