This book is based on the authors’ recent research results on formation control problems, including time-varying formation, communication delays, fault tolerant formation, for multiple UAV systems with highly nonlinear and coupled, parameters uncertainties, and external disturbances.
This book is based on the authors’ recent research results on formation control problems, including time-varying formation, communication delays, fault-tolerant formation for multiple UAV systems with highly nonlinear and coupled, parameter uncertainties, and external disturbances.
Differentiating from existing works, this book presents a robust optimal formation approach to designing distributed cooperative control laws for a group of UAVs, based on the linear quadratic regulator control method and the robust compensation theory. The proposed control method is composed of two parts: the nominal part to achieve desired tracking performance and the robust compensation part to restrain the influence of highly nonlinear and strongly coupled parameter uncertainties, and external disturbances on the global closed-loop control system. Furthermore, this book gives proof of their robust properties. The influence of communication delays and actuator fault tolerance can be restrained by the proposed robust formation control protocol, and the formation tracking errors can converge into a neighborhood of the origin bounded by a given constant in a finite time. Moreover, the book provides details about the practical application of the proposed method to design formation control systems for multiple quadrotors and tail-sitters. Additional features include a robust control method that is proposed to address the formation control problem for UAVs and theoretical and experimental research for the cooperative flight of the quadrotor UAV group and the tail-sitter UAV group.
Robust Formation Control for Multiple Unmanned Aerial Vehicles is suitable for graduate students, researchers, and engineers in the system and control community, especially those engaged in the areas of robust control, UAV swarming, and multi-agent systems.
| Preface |
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ix | |
| Authors |
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xi | |
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1 Introduction and Background |
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1 | (16) |
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1 | (1) |
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1.2 Literature Review on Formation Control for UAVs |
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2 | (9) |
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1.2.1 UAV Formation Experiment |
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2 | (5) |
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1.2.2 Research on UAV Formation Control Method |
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7 | (4) |
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11 | (4) |
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1.3.1 Introduction of Quadrotor Formation Hardware System |
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11 | (1) |
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12 | (1) |
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1.3.3 Indoor Positioning System Based on UWB Technology |
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13 | (1) |
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1.3.4 Communication Module |
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14 | (1) |
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15 | (2) |
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2 Robust Formation Control for Multiple Quadrotors with Nonlinearities and Disturbances |
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17 | (20) |
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17 | (2) |
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2.2 Preliminaries and Problem Formulation |
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19 | (5) |
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19 | (3) |
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2.2.2 Preliminaries on Graph Theory |
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22 | (1) |
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2.2.3 Problem Formulation |
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22 | (2) |
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2.3 Formation Protocol Design and System Analysis |
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24 | (7) |
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2.3.1 Position Controller Design |
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24 | (2) |
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2.3.2 Attitude Controller Design |
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26 | (1) |
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27 | (4) |
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2.4 Numerical Simulation Results |
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31 | (5) |
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36 | (1) |
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3 Robust Formation Trajectory Tracking Control for Multiple Quadrotors with Communication Delays |
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37 | (22) |
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37 | (2) |
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3.2 Preliminaries and Problem Formulation |
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39 | (3) |
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39 | (2) |
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3.2.2 Problem Formulation |
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41 | (1) |
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42 | (4) |
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3.3.1 Position Controller Design |
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42 | (3) |
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3.3.2 Attitude Controller Design |
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45 | (1) |
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3.4 Robustness Property Analysis |
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46 | (5) |
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51 | (5) |
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56 | (3) |
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4 Robust Formation Tracking Control for Multiple Quadrotors Subject to Switching Topologies |
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59 | (18) |
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59 | (2) |
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4.2 Preliminaries and Problem Description |
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61 | (3) |
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61 | (1) |
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62 | (2) |
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4.2.3 Problem Description |
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64 | (1) |
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4.3 Formation Control Protocol Design |
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64 | (3) |
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4.3.1 Position Controller Design |
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64 | (2) |
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4.3.2 Attitude Controller Design |
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66 | (1) |
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4.4 Global System Analysis |
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67 | (3) |
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70 | (5) |
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75 | (2) |
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5 Robust Time-Varying Formation Control for Tail-Sitters in Flight Mode Transitions |
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77 | (22) |
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77 | (2) |
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5.2 Preliminaries and Problem Statement |
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79 | (5) |
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5.2.1 Model of Tail-Sitter Aircraft |
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79 | (4) |
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5.2.2 Control Problem Statement |
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83 | (1) |
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5.3 Robust Formation Controller Design |
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84 | (3) |
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5.3.1 Trajectory Tracking Controller Design |
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85 | (1) |
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5.3.2 Attitude Controller Design |
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86 | (1) |
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5.4 Robust Property Analysis |
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87 | (5) |
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92 | (3) |
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95 | (4) |
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6 Robust Fault-Tolerant Formation Control for Tail-Sitters in Aggressive Flight Mode Transitions |
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99 | (22) |
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99 | (2) |
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101 | (7) |
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101 | (1) |
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6.2.2 Dynamic Motion Equations |
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102 | (4) |
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106 | (1) |
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107 | (1) |
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6.3 Robust Controller Design |
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108 | (2) |
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6.3.1 Outer Position Controller Design |
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108 | (1) |
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6.3.2 Inner Attitude Controller Design |
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109 | (1) |
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6.4 Robust Property Analysis |
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110 | (4) |
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114 | (5) |
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119 | (2) |
| Bibliography |
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121 | (8) |
| Index |
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129 | |
Hao Liu received the B.E. degree in control science and engineering from the Northwestern Polytechnical University, Xi'an, China, in 2008, the Ph.D. degree in automatic control from the Tsinghua University, Beijing, China, in 2013. In 2012, he was a visiting student in the Research School of Engineering, Australian National University. From 2013 to 2020, he has been with the School of Astronautics, Beihang University, Beijing, China, where he is currently an Associate Professor. Since 2020, he has been with the Institute of Artificial Intelligence, Beihang University, Beijing, China. From 2017 to 2018, he was a visiting scholar at the University of Texas at Arlington Research Institute, Fort Worth, USA. He received the best paper award on IEEE ICCA 2018. His research interests include formation control, reinforcement learning, robust control, nonlinear control, unmanned aerial vehicles, unmanned underwater vehicles, and multi-agent systems. He serves as an associate editor of Transactions of the Institute of Measurement and Control, and Advanced Control for Applications: Engineering and Industrial Systems.
Deyuan Liu received the B.E. degree in automation from the Beijing University of Chemical Technology, Beijing, China, in 2015, the Ph.D. degree in flight vehicle design from the School of Astronautics, Beihang University, Beijing, China, in 2021. He is currently a Postdoctoral Fellow of Zhuoyue Program in control theory and control engineering with Beihang University, Beijing, China. His current research interests include multi-agent systems, robust control, nonlinear control, formation control, and tail-sitter aircraft control.
Yan Wan is currently a Distinguished University Professor in the Electrical Engineering Department at the University of Texas at Arlington. She received her Ph.D. degree in Electrical Engineering from Washington State University in 2009 and then did postdoctoral training at the University of California, Santa Barbara. Her research interests lie in the modeling, evaluation, and control of large-scale dynamical networks, cyber-physical systems, stochastic networks, and their applications to smart grids, urban aerial mobility, autonomous driving, robot networking, and air traffic management. She is an appointed member of the Board of Governors of the IEEE Control Systems Society (CSS) and serves in the Conference Editorial Board and Technology Conference Editorial Board. She is also a technical committee member of AIAA Intelligent Systems, IEEE CSS Nonlinear Systems and Control, and IEEE CSS Networks and Communication Systems.
Frank L. Lewis is a Member of National Academy of Inventors, a Fellow of IEEE/IFAC/U.K/Institute of Measurement & Control, PE Texas, U.K. Chartered Engineer. He is a UTA Distinguished Scholar Professor, UTA Distinguished Teaching Professor, and Moncrief-O'Donnell Chair at the University of Texas at Arlington Research Institute. He received the bachelors degree in physics/EE in 1971 and the M.S.E.E. degree in 1971 from Rice University, Houston, TX, USA, the M.S. degree in aeronautical engineering in 1977 from the University of West Florida, Pensacola, FL, USA, and the Ph.D. degree in electrical engineering in 1981 from the Georgia Institute of Technology, Atlanta, GA, USA. He works in feedback control, intelligent systems, cooperative control systems, and nonlinear systems. He is author of 7 U.S. patents, numerous journal special issues, journal papers, and 20 books, including Optimal Control, Aircraft Control, Optimal Estimation, and Robot Manipulator Control which are used as university textbooks worldwide. He received the Fulbright Research Award, NSF Research Initiation Grant, ASEE Terman Award, Int. Neural Network Soc. Gabor Award, U.K. Inst Measurement & Control Honeywell Field Engineering Medal, IEEE Computational Intelligence Society Neural Networks Pioneer Award, AIAA Intelligent Systems Award. Received Outstanding Service Award from Dallas IEEE Section, selected as Engineer of the year by Ft. Worth IEEE Section. Was listed in Ft. Worth Business Press Top 200 Leaders in Manufacturing. Texas Regents Outstanding Teaching Award 2013.
Kimon P. Valavanis received the Diploma degree in electrical and electronic engineering from the National Technical University of Athens, Athens, Greece, in 1981, and the M.Sc. degree in electrical engineering and the Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute, Troy, NY, USA, in 1984 and 1986, respectively. He is currently a Professor and the Chair of the Electrical and Computer Engineering Department, and also the Acting Chair of the Computer Science Department, University of Denver, Denver, CO, USA. His current research interests include unmanned systems and distributed intelligence systems.
