Optimizing Flight Control of Unmanned Aerial Vehicles with Physics-Based Reliability Models

The use of unmanned aerial vehicles (UAVs) is rapidly expanding across numerous industries, with a diverse range of applications. Ensuring reliable operation is crucial for safety, costs, and customer satisfaction, especially in the aviation sector. This paper presents a novel approach to optimizing flight control by incorporating a reliability-based control allocation system with physics-based reliability models. More specifically, the control allocation is based on physical estimations of reliability parameters. The reliability model incorporates a Weibull distribution reformulated to express reliability as a function of cumulated damage instead of time. The failure mechanisms of the rotor components are modeled based on physics, allowing for the calculation of cumulated damages as a function of the UAV's operation. The parameterization of the reliability and failure mechanism models is entirely based on publicly available manufacturer catalog data to ensure that the models are readily applicable to new designs with off-the-shelf components. Additionally, this approach facilitates the verification and validation of the models. The developed integrated control strategy and physics-based models have been implemented in Matlab-Simulink and applied to the case study of a coaxial quadrotor UAV for validation. When applied to the case study, the controller efficiently redistributes the control duties of rotors with a high probability of failure while maintaining the desired system response, thus increasing the operation's reliability.