Advanced Control System Architectures for Rotorcraft Uncrewed Aerial Vehicles

This work explores adaptive control techniques to increase the safety of uncrewed aircraft during flight. The widespread diffusion of this type of aircraft has reached many fields of application. In recent years, a significant increase has been observed in both the civil and military sectors, with applications ranging from surveillance to agriculture and goods transportation. The expected large scale use of these aircraft will also occur over densely populated areas, requiring the development of advanced and robust control techniques capable of guaranteeing system safety. In particular, this thesis explores the application of adaptive control systems for rotary-wing aircraft such as helicopters, ducted fans, and multirotors. The techniques examined proved effective in ensuring the required flight performance both under atmospheric disturbances and in the event of failures. The adaptive approach allows the control system to modify its parameters in real time in response to changes in weather conditions and flight phases. This capability is particularly useful for addressing challenges posed by adverse weather and control-surface malfunctions, which can compromise stability and flight safety and potentially cause damage to property or people. Furthermore, adaptive control improves the operational efficiency of unmanned aircraft by optimizing performance for different missions and operational contexts. The techniques analyzed belong to the family of adaptive control methods known as Model Reference Adaptive Control (MRAC). This class of adaptive control directly estimates a control input capable of compensating for differences between the measured aircraft performance and the expected or desired performance. In particular, L1 adaptive control, an evolution of MRAC capable of guaranteeing faster compensation for disturbances and unknown dynamics, is applied in this thesis to improve the flight performance of a small unmanned helicopter. The same technique is also applied to guarantee safe flight for a ducted-fan aircraft, even in the event of the loss of a control surface. Additionally, an adaptive algorithm is developed that combines information on hexacopter thruster effectiveness, obtained from MRAC, with a Kalman filter. This algorithm has been shown to improve flight performance and to ensure continued flight capability even in the event of failure of one of the thrusters.