This book focuses on the fault-tolerant cooperative control (FTCC) of multiple unmanned aerial vehicles (multi-UAVs). It provides systematic and comprehensive descriptions of FTCC issues in multi-UAVs concerning faults, external disturbances, strongly unknown nonlinearities, and input saturation. Further, it addresses FTCC design from longitudinal motions to attitude motions, and outer-loop position motions of multi-UAVs. The book’s detailed control schemes can be used to enhance the flight safety of multi-UAVs. As such, the book offers readers an in-depth understanding of UAV safety in cooperative/formation flight and corresponding design methods. The FTCC methods presented here can also provide guidelines for engineers to improve the safety of aerospace engineering systems. The book offers a valuable asset for scientists and researchers, aerospace engineers, control engineers, lecturers and teachers, and graduates and undergraduates in the system and control community, especially those working in the field of UAV cooperation and multi-agent systems.
This book provides a comprehensive overview of recent advances in the analysis and design of health management systems for cooperating unmanned aerial vehicles. Such systems rely upon monitoring and fault adaptation schemes. Motivation for their study comes from the fact that, despite the use of fault-tolerant control software and hardware embedded onboard air vehicles, overall fleet performance may still be degraded after the occurrence of anomalous events such as systems faults and failures. Cooperative health management (CHM) systems seek to provide adaptation to the presence of faults by capitalizing on the availability of interconnected computing, sensing and actuation resources.This monograph complements the proposed CHM concepts by means of case studies and application examples. It presents fundamental principles and results encompassing optimization, systems theory, information theory, dynamics, modeling and simulation. Written by pioneers in cooperative control, health management and fault-tolerant control for unmanned systems, this book is a unique source of information for designers, researchers and practitioners interested in the field.
Unmanned aerial vehicles (UAVs) are critical components of the future naval forces. UAV control and monitoring with autonomous operation will become an absolute necessity and adaptive cooperation of vehicles is the only practical alternative. The objective of this project is to develop and evaluate new methodologies for cooperative (formation) control of multiple unmanned air vehicles. The goal is to have multiple UAVs working together as a group. Instead of separately assigning distinct tasks to each vehicle, the operator would assign tasks to the UAV group, which then determines the best way to accomplish each task, freeing the operator to maintain surveillance over the entire operation. In this project we investigated Path Tracking and obstacle avoidance of UAVs using fuzzy logic method. Algorithms for close formation control of multi-UAVs are developed and simulated. We also investigated fault-tolerant control of single UAVs by neuro-adaptive method. Detailed description of this method is provided in this document. The project has supported S graduate students with 9 technical papers published.
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.
This book offers a complete overview of fault-tolerant flight control techniques. Discussion covers the necessary equations for the modeling of small UAVs, a complete system based on extended Kalman filters, and a nonlinear flight control and guidance system.
“Fault Detection and Isolation: Multi-Vehicle Unmanned System” deals with the design and development of fault detection and isolation algorithms for unmanned vehicles such as spacecraft, aerial drones and other related vehicles. Addressing fault detection and isolation is a key step towards designing autonomous, fault-tolerant cooperative control of networks of unmanned systems. This book proposes a solution based on a geometric approach, and presents new theoretical findings for fault detection and isolation in Markovian jump systems. Also discussed are the effects of large environmental disturbances, as well as communication channels, on unmanned systems. The book proposes novel solutions to difficulties like robustness issues, as well as communication channel anomalies. “Fault Detection and Isolation: Multi-Vehicle Unmanned System” is an ideal book for researchers and engineers working in the fields of fault detection, as well as networks of unmanned vehicles.
Aerospace vehicles are by their very nature a crucial environment for safety-critical systems. By virtue of an effective safety control system, the aerospace vehicle can maintain high performance despite the risk of component malfunction and multiple disturbances, thereby enhancing aircraft safety and the probability of success for a mission. Autonomous Safety Control of Flight Vehicles presents a systematic methodology for improving the safety of aerospace vehicles in the face of the following occurrences: a loss of control effectiveness of actuators and control surface impairments; the disturbance of observer-based control against multiple disturbances; actuator faults and model uncertainties in hypersonic gliding vehicles; and faults arising from actuator faults and sensor faults. Several fundamental issues related to safety are explicitly analyzed according to aerospace engineering system characteristics; while focusing on these safety issues, the safety control design problems of aircraft are studied and elaborated on in detail using systematic design methods. The research results illustrate the superiority of the safety control approaches put forward. The expected reader group for this book includes undergraduate and graduate students but also industry practitioners and researchers. About the Authors: Xiang Yu is a Professor with the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. His research interests include safety control of aerospace engineering systems, guidance, navigation, and control of unmanned aerial vehicles. Lei Guo, appointed as "Chang Jiang Scholar Chair Professor", is a Professor with the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. His research interests include anti-disturbance control and filtering, stochastic control, and fault detection with their applications to aerospace systems. Youmin Zhang is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, Québec, Canada. His research interests include fault diagnosis and fault-tolerant control, and cooperative guidance, navigation, and control (GNC) of unmanned aerial/space/ground/surface vehicles. Jin Jiang is a Professor in the Department of Electrical & Computer Engineering, Western University, London, Ontario, Canada. His research interests include fault-tolerant control of safety-critical systems, advanced control of power plants containing non-traditional energy resources, and instrumentation and control for nuclear power plants.
Unmanned aerial vehicles (UAVs) are increasingly used in military missions because they have the advantages of not placing human life at risk and of lowering operation costs via decreased vehicle weight. These benefits can be fully realized only if UAVs work cooperatively in groups with an efficient exchange of information. This book provides an authoritative reference on cooperative decision and control of UAVs and the means available to solve problems involving them.
Since several decades ago, unmanned aerial vehicles (UAVs) have attracted a great deal of attention in academic, industrial and military communities. Recently, multiple cooperative UAVs have been applied in various applications such as forest fire detection and fighting, search and exploration, environmental monitoring and surveillance.The main objectives of this dissertation are to design novel algorithms for single quadrotor UAV trajectory tracking control and multiple UAVs for cooperative/formation control. Then, applying these algorithms in forest monitoring and fire detection application, where a group of detection UAVs is required to surround and track the fire perimeter for monitoring and observation mission. Furthermore, a new algorithm for fault-tolerant cooperative control (FTCC) is proposed, in order to mitigate potential UAV fault effect for reliable and safe mission completion. Finally, a fire fighting algorithm is developed for achieving minimum distances for forest fire UAVs to arrive at their assigned fire spots destinations. A combination of sliding mode control (SMC) and linear quadratic regulator (LQR) is used to design a single quadrotor UAV controller, which is then used to design a formation controller of multiple UAVs. Moreover, another formation controller is designed based on SMC to achieve robust formation control against modeling uncertainties and disturbances.Cooperative UAVs are applied in forest monitoring and fire detection application through three stages: search, confirmation and observation. UAVs are assigned to search for potential forest fires in a certain area, once a fire is detected and a fire alarm will be generated by one or more of the UAVs. The UAVs team then reconfigures its formation by following an elliptic fire perimeter, calculated by the ground station (GS) using a fire spread model. Afterward, the fire alarm confirmation stage begins and all UAVs start evenly distributed for surrounding the fire spot according to the UAVs number in the team. When the fire alarm is confirmed, the observation stage starts and UAVs continue tracking the fire along the fire perimeter. SMC is used to design a formation reconfigurable controller to switch between a predefined formation shape during the search stage, to a dynamic surrounding formation. This controller guarantees even distribution of UAVs surrounding the fire spots and the robustness against disturbances. In addition, task assignment is used with multiple fire spots and multiple UAVs teams in order to reduce the mission execution time. Moreover, the proposed control algorithms are implemented to a team of UAVs paired with a team of unmanned ground vehicles (UGVs), by using these UGVs as a take-off and landing platform in forest monitoring and fire detection application.Meanwhile, UAVs may need to leave formation for refueling/recharging during the mission of search, confirmation and observation, or if a fault occurred during the mission due to fire flames, heat or UAV's internal fault sources. Therefore, an FTCC algorithm is designed based on the graph theory to mitigate the fault effect on mission completion, and ensure complete surrounding and data gathering of the fire spots using different fire sensors such as infrared cameras, charge-coupled devices (CCD) cameras and thermal cameras etc.Afterward, data gathered during observation stage are processed in the GS, then dangerous fire spots coordinates are sent to the fire fighting UAVs. The leader UAV, the GS or both can perform the task assignment process using an auction-based or Hungarian algorithms to assign each UAV to a fire spot for deploying fire suppressant. Furthermore, a hybrid approach of control parametrization and time discretization (CPTD) and particle swarm optimization (PSO) is proposed to achieve minimum flight distance for each UAV to arrive at its destination, minimizing fuel/battery consumption. Since PSO cannot solve the continuous control inputs, CPTD is used to provide an approximate piecewise linearization of the control inputs. Thus, PSO can be adopted to achieve the global optimum solution.Finally, the proposed algorithms are being implemented on single and multiple quadrotor UAVs in simulations. While, the leader-follower approach is used in cooperative control in a decentralized manner to avoid the disadvantages of centralization. Thereafter, the proposed algorithms are verified on a set of Qball-X4 quadrotor UAVs and QGV unmanned ground vehicles (UGVs) platforms in real-time experiments through different scenarios.
Time-Critical Cooperative Control of Autonomous Air Vehicles presents, in an easy-to-read style, the latest research conducted in the industry, while also introducing a set of novel ideas that illuminate a new approach to problem-solving. The book is virtually self-contained, giving the reader a complete, integrated presentation of the different concepts, mathematical tools, and control solutions needed to tackle and solve a number of problems concerning time-critical cooperative control of UAVs. By including case studies of fixed-wing and multirotor UAVs, the book effectively broadens the scope of application of the methodologies developed. This theoretical presentation is complemented with the results of flight tests with real UAVs, and is an ideal reference for researchers and practitioners from academia, research labs, commercial companies, government workers, and those in the international aerospace industry. Addresses important topics related to time-critical cooperative control of UAVs Describes solutions to the problems rooted in solid dynamical systems theory Applies the solutions developed to fixed-wing and multirotor UAVs Includes the results of field tests with both classes of UAVs
