Journal ArticleDOI
Sliding mode observers for fault detection and isolation
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This paper considers the application of a particular sliding mode observer to the problem of fault detection and isolation using the equivalent output injection concept to explicitly reconstruct fault signals.About:
This article is published in Automatica.The article was published on 2000-04-01. It has received 1141 citations till now. The article focuses on the topics: Fault detection and isolation & Stuck-at fault.read more
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Journal ArticleDOI
Brief paper: Nonlinear robust fault reconstruction and estimation using a sliding mode observer
TL;DR: This paper considers fault detection and estimation issues for a class of nonlinear systems with uncertainty, using an equivalent output error injection approach, and a particular design of sliding mode observer is presented for which the parameters can be obtained using LMI techniques.
Journal ArticleDOI
Sliding mode observers: a survey
TL;DR: The equivalent injection signal in problems relating to fault detection and condition monitoring is demonstrated and the literature in the area is presented and qualified in the context of continuing developments in the broad areas of the theory and application of sliding mode observers.
Journal ArticleDOI
From Model, Signal to Knowledge: A Data-Driven Perspective of Fault Detection and Diagnosis
Xuewu Dai,Zhiwei Gao +1 more
TL;DR: An outlook to the possible evolution of FDD in industrial automation, including the hybrid FDD and the emerging networked FDD, are presented to reveal the future development direction in this field.
Journal ArticleDOI
Observer-based adaptive sliding mode control for nonlinear Markovian jump systems
TL;DR: An integral sliding mode surface and observer-based adaptive sliding mode controller is designed such that the MJSs are insensitive to all admissible uncertainties and satisfy the reaching condition and the stochastic stability of the closed-loop system can be guaranteed.
Journal ArticleDOI
Sliding mode observers for robust detection and reconstruction of actuator and sensor faults
Chee Pin Tan,Christopher Edwards +1 more
TL;DR: In this paper, the authors describe a method for designing sliding mode observers for detection and reconstruction of actuator and sensor faults, that is robust against system uncertainty, using ℋ∞ concepts to design the sliding motion so that an upper bound on the effect of the uncertainty on the reconstruction of the faults will be minimized.
References
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Book
Sliding Modes in Control and Optimization
TL;DR: The theory and practical application of Lyapunov's Theorem, a method for the Study of Non-linear High-Gain Systems, are studied.
Journal ArticleDOI
Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results
TL;DR: In this article, the authors review the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and present some new results with emphasis on the latest attempts to achieve robustness with respect to modelling errors.
Journal ArticleDOI
Paper: A survey of design methods for failure detection in dynamic systems
TL;DR: This paper surveys a number of methods for the detection of abrupt changes in stochastic dynamical systems, focusing on the class of linear systems, but the basic concepts carry over to other classes of systems.
A survey of design methods for failure detection in dynamic systems
TL;DR: A number of methods for detecting abrupt changes (such as failures) in stochastic dynamical systems are surveyed in this paper, where tradeoffs in complexity versus performance are discussed, ranging from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, and the development of jump process formulations.
BookDOI
Issues of Fault Diagnosis for Dynamic Systems
TL;DR: In this paper, the issues of fault diagnosis for dynamic systems (including fault detection and isolation) has become an important topic of research and many applications of qualitative and quantitative modelling, statistical processing and neural networks are now being planned and developed in complex engineering systems.