![]() Docking stations can solve the battery endurance issue and put UAVs one step ahead in autonomous systems.Īt present, UAVs are being used in multiple military, industrial and commercial applications, as shown in Fig. Another promising solution is a docking station, which can recharge or swap batteries, store and even perform communication tasks with UAVs. This issue can be mitigated through the design of different types of batteries using hybrid systems or internal combustion engines. ![]() The main critical limitation among UAVs is flight endurance, which is limited due to the limited power supply provided by batteries. There are several limitations to the practical implementation of UAVs in different application scenarios. Other types of UAVs are also reported, but their numbers are comparably low. Most of the studies report multirotors due to their simplicity in control mechanisms and high-precision in positioning. Unmanned aerial vehicles (UAVs), also known as drones, are being widely used and have gained significant attention in the last decade. We believe these insights will serve as guidelines and motivations for relevant researchers. Finally, future research directions are identified to further hone the research work. Moreover, application scenarios, potential challenges and security issues are also examined. This study provides a comprehensive review of UAVs, types, swarms, classifications, charging methods and regulations. As a result, the primary goal of this research is to provide insights into the potentials of UAVs, as well as their characteristics and functionality issues. Despite these appealing benefits, UAVs face limitations in operability due to several critical concerns in terms of flight autonomy, path planning, battery endurance, flight time and limited payload carrying capability, as intuitively it is not recommended to load heavy objects such as batteries. UAVs support implicit particularities including access to disaster-stricken zones, swift mobility, airborne missions and payload features. It is due to technological trends and rapid advancements in control, miniaturization, and computerization, which culminate in secure, lightweight, robust, more-accessible and cost-efficient UAVs. The drone industry has seen a sharp uptake in the last decade as a model to manufacture and deliver convergence, offering synergy by incorporating multiple technologies. They appear in great diversity in a multiplicity of applications for economic, commercial, leisure, military and academic purposes. Simulations of larger faults showed that increased errors in the LQ controller lead to rough control signals this weakens the robustness of the FTCS.Recently, unmanned aerial vehicles (UAVs) or drones have emerged as a ubiquitous and integral part of our society. However, the kinematic controller increased the bandwidth substantially accurate control was achieved within the extended bandwidth. Because of a narrow control bandwidth of the LQ controller, optimal control was not achieved for larger faults. In a fault situation, fault accommodation is chosen for feedback control. Multiple faults during a simulation were also accurately detected. The results from the FDI showed that there were large separations between simulations with and without faults. The control system gave excellent reference tracking.Parity space is chosen as the FDI method and variance testing is implemented for residual validation. This resulted in extended control bandwidth which increased the robustness of the AFCS. It was necessary to implement a kinematic controller to reduce stationary errors. The AFCS is tested separately in fault-free conditions.The AFCS comprises of lookahead-based steering for guidance and a linearquadratic (LQ) velocity and rate controller for reference tracking. Several case studies test the capabilities of the FTCS using a variety of faults in the absence of noise and disturbances. The literature study reviews methods for fault-tolerant control and also discusses important faults and failures related to UAVs.The FTCS is implemented in MATLAB Simulink with a nonlinear model of the Cessna 172SP as a simulation plant. The goals are to develop an automatic-flight control system (AFCS) with fault detection and isolation (FDI) and a reconfiguration mechanism for accommodation of faults. The main focus of this master s thesis is fault-tolerant control systems (FTCSs) for unmanned aerial vehicles (UAVs).
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