Brief paper: LMI-based sensor fault diagnosis for nonlinear Lipschitz systems

Authors:
A. M. Pertew;H. J. Marquez;Q. Zhao
Affiliations:
Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada T6G 2V4;Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada T6G 2V4;Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada T6G 2V4
Venue:
Automatica (Journal of IFAC)
Year:
2007

Citing 7
Cited 5

Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results

Automatica (Journal of IFAC)
A bilinear fault detection observer

Automatica (Journal of IFAC)
On the use of adaptive updating rules for actuator and sensor fault diagnosis

Automatica (Journal of IFAC)
Robust model-based fault diagnosis for dynamic systems

Robust model-based fault diagnosis for dynamic systems
Paper: A survey of design methods for failure detection in dynamic systems

Automatica (Journal of IFAC)
Brief An LMI approach to design robust fault detection filter for uncertain LTI systems

Automatica (Journal of IFAC)
Optimal stochastic fault detection filter

Automatica (Journal of IFAC)

Zero assignment for robust H2/H∞ fault detection filter design

IEEE Transactions on Signal Processing
Brief paper: Observer-based control of a class of time-delay nonlinear systems having triangular structure

Automatica (Journal of IFAC)
On design of quantized fault detection filters with randomly occurring nonlinearities and mixed time-delays

Signal Processing
Integrated Design of Observer Based Fault Detection for a Class of Uncertain Nonlinear Systems

International Journal of Applied Mathematics and Computer Science - Issues in Advanced Control and Diagnosis
Sensor diagnosis and state estimation for a class of skew symmetric time-varying systems

Automatica (Journal of IFAC)

Quantified Score

Hi-index	22.15

Visualization

Abstract

The problem of sensor fault diagnosis in the class of nonlinear Lipschitz systems is considered. A dynamic observer structure is used with the objective to make the residual converge to the faults vector achieving detection and estimation at the same time. It is shown that, unlike the classical constant gain structure, this objective is achievable by minimizing the faults effect on the estimation error of the dynamic observer. The use of appropriate weightings to solve the design problem in a standard convex optimization framework is also demonstrated. An LMI design procedure solvable using commercially available software is presented.