Automatica (Journal of IFAC)
Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Robot Dynamics and Control
Diagnosis and Fault-Tolerant Control
Diagnosis and Fault-Tolerant Control
Brief paper: Nonlinear robust fault reconstruction and estimation using a sliding mode observer
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Isolation and handling of actuator faults in nonlinear systems
Automatica (Journal of IFAC)
International Journal of Systems Science
Brief paper: On the use of adaptive updating rules for actuator and sensor fault diagnosis
Automatica (Journal of IFAC)
Sliding mode observers for fault detection and isolation
Automatica (Journal of IFAC)
Nonlinear system fault diagnosis based on adaptive estimation
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
A Diagnostic Thau Observer for a Class of Unmanned Vehicles
Journal of Intelligent and Robotic Systems
Automatica (Journal of IFAC)
Hi-index | 22.15 |
This paper presents a fault detection and isolation (FDI) scheme for a class of Lipschitz nonlinear systems with nonlinear and unstructured modeling uncertainty. This significantly extends previous results by considering a more general class of system nonlinearities which are modeled as functions of the system input and partially measurable state variables. A new FDI method is developed using adaptive estimation techniques. The FDI architecture consists of a fault detection estimator and a bank of fault isolation estimators. The fault detectability and isolability conditions, characterizing the class of faults that are detectable and isolable by the proposed scheme, are rigorously established. The fault isolability condition is derived via the so-called fault mismatch functions, which are defined to characterize the mutual difference between pairs of possible faults. A simulation example of a single-link flexible joint robot is used to illustrate the effectiveness of the proposed scheme.