Sensor fault diagnosis using a non‐homogeneous high‐order sliding mode observer with application to a transport aircraft

Abstract

In avionics and aerospace multisensor systems, reliable and early detection of individual sensor faults present substantial challenges to health monitoring designers of such systems. This study addresses the problem of sensor fault diagnosis. The proposed solution is based on a non-homogeneous high-order sliding mode observer used to estimate the faults, theoretically in finite time and in the presence of bounded disturbances. The sensor faults are estimated for the class of systems satisfying the structural property of strong observability. A key feature of the proposed solution is concerned by the effect that measurement noise could have on fault reconstruction. It is shown that the fault estimation error is bounded in the L ∞ -norm sense, and an upper bound is theoretically derived. The method is applied to the problem of sensor fault estimation of a large transport aircraft. Simulation results as well as a pilot experiment are presented to demonstrate the potential of the proposed method.

Iterative learning scheme to design intermittent fault estimators for nonlinear systems with parameter uncertainties and measurement noise

“…1,2 They can possibly cause the degeneration performance and even induce serious damages. Generally, fault detection, 5,6 which detects the occurrence of the fault by analyzing a residual signal, becomes particularly important in the modern industrial control system. Generally, fault detection, 5,6 which detects the occurrence of the fault by analyzing a residual signal, becomes particularly important in the modern industrial control system.…”

“…In real applications, parameter uncertainties 11,12 are caused by linearization and model reduction, which may influence significantly the performance of fault estimation schemes. Among various types of fault estimation methods that have been developed, observer-based methods have been proven as effective techniques for systems with parameters uncertainties, such as sliding-mode observer (SMO), 6,13 adaptive observer (AO), 15,16 and intermediate observer. 13,14 To cope with these problems, a number of research results available in the literature are presented to estimate the fault signals.…”

“…Up to now, many research works on faults have been reported in the literature, 3,4 where fault detection and fault estimation are the most popular ones. Generally, fault detection, 5,6 which detects the occurrence of the fault by analyzing a residual signal, becomes particularly important in the modern industrial control system. However, it is difficult to obtain the exact information of the faults.…”

“…13,14 To cope with these problems, a number of research results available in the literature are presented to estimate the fault signals. Among various types of fault estimation methods that have been developed, observer-based methods have been proven as effective techniques for systems with parameters uncertainties, such as sliding-mode observer (SMO), 6,13 adaptive observer (AO), 15,16 and intermediate observer. 17,18 However, these methods have some disadvantages that are hard to satisfy specified conditions for many practical systems.…”

Robust Output Tracking of a 3DOF Helicopter via High-Order Sliding Mode Observers

“…those which appear implicitly at the input channels [7]. This property has been taken into account to withstand with actuator faults in a wide class of applications, [3,8,9,10]. In [8], fault detection and isolation is achieved by means of a residual generation scheme and thresholds definition.…”