Smac–Fdi: A Single Model Active Fault Detection and Isolation System for Unmanned Aircraft

• Main Author: Ducard Guillaume J.J.
• Format: Article
• Language: English
• Published: Sciendo 2015-03-01
• Series: International Journal of Applied Mathematics and Computer Science
• Subjects: fault detection and isolation; unmanned aerial vehicles; kalman filtering; computationally efficient diagnosis system; active fault diagnosis; artificial excitation system
• Online Access: https://doi.org/10.1515/amcs-2015-0014

This article presents a single model active fault detection and isolation system (SMAC-FDI) which is designed to efficiently detect and isolate a faulty actuator in a system, such as a small (unmanned) aircraft. This FDI system is based on a single and simple aerodynamic model of an aircraft in order to generate some residuals, as soon as an actuator fault occurs. These residuals are used to trigger an active strategy based on artificial exciting signals that searches within the residuals for the signature of an actuator fault. Fault isolation is carried out through an innovative mechanism that does not use the previous residuals but the actuator control signals directly. In addition, the paper presents a complete parameter-tuning strategy for this FDI system. The novel concepts are backed-up by simulations of a small unmanned aircraft experiencing successive actuator failures. The robustness of the SMAC-FDI method is tested in the presence of model uncertainties, realistic sensor noise and wind gusts. Finally, the paper concludes with a discussion on the computational efficiency of the method and its ability to run on small microcontrollers.