The monograph explores the safety of unmanned flight vehicles via the corresponding fault-tolerant control design methods. The authors analyse the safety control issues of unmanned flight vehicles, which include finite-time recovery against faults, concurrence of actuator faults and sensor faults, concurrence of actuator faults and wind effects, and faults encountered by a portion of unmanned flight vehicles in a distributed communication network. In addition, the commonly used simple but effective proportional-integral-derivative structure is also incorporated into the safety control…mehr
The monograph explores the safety of unmanned flight vehicles via the corresponding fault-tolerant control design methods.
The authors analyse the safety control issues of unmanned flight vehicles, which include finite-time recovery against faults, concurrence of actuator faults and sensor faults, concurrence of actuator faults and wind effects, and faults encountered by a portion of unmanned flight vehicles in a distributed communication network. In addition, the commonly used simple but effective proportional-integral-derivative structure is also incorporated into the safety control design for unmanned flight vehicles. By using the fractional-order calculus, the developed safety control results are able to ensure flight safety and achieve the refined performance adjustments against faults and wind effects.
The book will be of interest to 3rd/4th year undergraduate students, postgraduate and graduate students, researchers, academic staff, engineers of aircraft and unmanned flight vehicles.
Ziquan Yu is currently affiliated with College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China. His current research interests include fractional-order control, fault-tolerant cooperative control of safety-critical systems, and guidance, navigation, and control of unmanned flight vehicles. Youmin Zhang is currently affiliated with Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, Quebec, Canada. His current research interests include guidance, navigation, and control, fault detection and diagnosis, fault-tolerant control, and remote sensing with applications to unmanned aerial/space/ground/marine vehicles, smart grids, smart cities, and cyber-physical systems. Bin Jiang is currently affiliated with College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China. His current research interests include fault diagnosis and fault-tolerant control and their applications. Chun-Yi Su is currently affiliated with Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, Quebec, Canada. His current research interests include the application of automatic control theory to mechanical systems, especially the control of systems involving hysteresis nonlinearities.
Inhaltsangabe
1. Introduction 2. Preliminaries 3. Refined Finite-Time FO FTC of UAV Against Input Saturation and Actuator Faults 4. Refined FO Adaptive Safety Control of UAVs Against Actuator-Sensor Faults 5. Composite Refined FO Safety Control of UAVs Against Actuator Faults and Wind Effects 6. Refined FO Adaptive Safety Control of UAVs Against Actuator Faults and Wind Effects 7. FO PID-Based Refined Adaptive Safety Control of UAVs 8. Refined Distributed Adaptive FO Safety Control of Multiple UAVs 9. Refined Distributed FO Adaptive Safety Control of Two-Layer Uas 10. Conclusions and Future Research Directions
1. Introduction 2. Preliminaries 3. Refined Finite-Time FO FTC of UAV Against Input Saturation and Actuator Faults 4. Refined FO Adaptive Safety Control of UAVs Against Actuator-Sensor Faults 5. Composite Refined FO Safety Control of UAVs Against Actuator Faults and Wind Effects 6. Refined FO Adaptive Safety Control of UAVs Against Actuator Faults and Wind Effects 7. FO PID-Based Refined Adaptive Safety Control of UAVs 8. Refined Distributed Adaptive FO Safety Control of Multiple UAVs 9. Refined Distributed FO Adaptive Safety Control of Two-Layer Uas 10. Conclusions and Future Research Directions
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