For a growing number of flight operations, human piloted aircraft are being replaced by au- tonomous uncrewed aerial vehicles (UAVs) which can provide equivalent service with drastically reduced operating costs. The UAVs that are deployed in mission critical applications, such as search and rescue, medical deliveries to remote locations, infrastructure inspection, and reconnaissance and surveillance, must be extremely resilient as the loss of a vehicle poses significant threats to financial, security, or personnel interests. In order to rely on uncrewed systems in these mission critical situations, we must have confidence in their ability to perform their duties as reliably as possible. Recent advancements in hardware, software, and control design have increased the re- liability of these small inexpensive aircraft. The focus of this dissertation is to further improve multi-rotor reliability in the presence of a broad class of disturbances, while providing a unifying framework that can be extended to multiple applications.The methods we present in this work are based on a feedback linearizing control strategy in which the controller is augmented with an extended high-gain observer. The addition of the extended high-gain observer allows us to overcome the typical drawbacks associated with using a feedback linearization control approach; primarily that we must have an excellent model of the system, and we must know any disturbances that are affecting the system. The extended high-gain observer not only provides estimates of any model uncertainties or external disturbances, but also any unmeasured states for use in output feedback control. This estimation and control strategy enables the multi-rotor to robustly track a trajectory in the presence of a broad class of unmodeled disturbances and without needing an extremely accurate system model. This method forms the base technology applied throughout this dissertation. We extend our estimation and control strategy in a number of ways in the coming chapters. We begin by extending the observer dynamics further to incorporate real-time trajectory estimation for a reference system which may have partially known or completely unknown dynamics, and for which we assume we only have access to the position of the reference system. The observer is then able to provide estimates of all higher-order trajectory terms required for feedforward control, improving transient tracking performance. We further extend this strategy to enable both the detection and classification of a complete actuator failure of a multi-rotor during flight. The identification subsequently enables a control reconfiguration and a recovery from the loss of an actuator to resume flight operations. This extension provides the ability to not only detect and correctly identify a failure, but to discern the failure from other external disturbances affecting the system during flight. Finally, we extend our estimation and control strategy to enable robust trajectory tracking for a novel form of multi-body multi-rotor systems. This type of system consists of a large carrier UAV which suspends a small platform which is itself actuated by a pair of rotors. The platform is equipped with a manipulator which enables long reach aerial manipulation. One advantage of this configuration is the workspace will not be disturbed by downwash from the carrier UAV. Each of these methods are rigorously analyzed to guarantee closed-loop stability and provide insights into the trade-offs that arise during the design process for these control systems utilizing extended high-gain observers.
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