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

Abstract

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.

Fault Detection of Multi Wheeled Robot Consensus Based on EKF

“…Additionally, [12] introduces a Kalman filter designed for joint state prediction and unknown input estimation within linear stochastic discrete-time systems subject to intermittent unknown inputs in measurements. Interests in FDI for nonlinear systems have grown significantly in recent years due to the fact that most of the systems, we face in practice, are nonlinear in nature such as [13] where the FDI system is based on a single model EKF filter that generates residuals as soon as the behavior of the aircraft deviates from expected, also [14] directs its focus towards fault detection in wheeled mobile robots utilizing an EKF filter. The fault detection process typically involves two primary steps: residual generation and subsequent residual evaluation.…”

Fault Detection in Nonlinear Systems Via Linear Methods

“…Various models of technical systems have been investigated: linear, polynomial, nonlinear, descriptor, and hybrid. Many practical examples have been considered; in particular, special books have been devoted to industrial systems (Boulkroune et al, 2013;Caccavale and Villiani, 2002;Ducard, 2015;Filaretov et al, 2003;Russell et al, 2001).…”