Model-Based Detection and Isolation of Rudder Faults for a Small UAS

New regulatory safety standards will soon require unmanned aircraft systems to meet high levels of reliability. There is potential to increase the reliability of such systems without necessarily increasing the number of hardware components. This paper motivates a mix of physical and analytical redundancy in order to increase the system-level reliability of a small unmanned aircraft. The aircraft discussed in this paper has a split rudder for fault-tolerant control. Hardware faults, such as a stuck rudder, need to be detected and isolated in real-time in order for the controller to be reconfigured. In this paper, flight dynamics principles are used to design a model-based filter for detecting and isolating stuck faults in the split rudder of the aircraft. A classical controller is developed in order to make the aircraft robust to stuck rudder faults. The performance and robustness of the filter is evaluated, in closed-loop, through high fidelity simulations. The results in this paper highlight the potential for increasing the reliability of safety-critical aviation systems through analytical redundancy.