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Journal ArticleDOI

Design of unknown input observers and robust fault detection filters

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TLDR
In this article, the authors proposed a new approach to design robust (in the disturbance de-coupling sense) fault detection filters which ensure that the residual vector, generated by this filter, has both robust and directional properties.
Abstract
Fault detection filters are a special class of observers that can generate directional residuals for the purpose of fault isolation. This paper proposes a new approach to design robust (in the disturbance de-coupling sense) fault detection filters which ensure that the residual vector, generated by this filter, has both robust and directional properties. This is done by combining the unknown input observer and fault detection filter principles. The paper proposes a new full-order unknown input observer, and gives necessary and sufficient conditions for its existence. After the disturbance de-coupling conditions are satisfied, the remaining design freedom can be used to make the residual have the directional property, based on the fault detection filter principle. A nonlinear jet engine system is used to illustrate the robust fault isolation approach presented. It is shown that linearization errors can be approximately treated as unknown disturbances and be de-coupled in the design of a robust fault detect...

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Citations
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Proceedings ArticleDOI

Design of full order unknown input observers with H/sub /spl infin// performance

F. Amato, +1 more
TL;DR: In this paper, the authors propose a procedure that allows one to design an unknown input observer decoupling, where possible, the disturbance input from the estimation error, and minimising the effect of the remaining disturbances in an H/sub /spl infin// sense.
Proceedings ArticleDOI

Unknown Input Observers for a class of distributed parameter systems

TL;DR: In this article, an unknown input observer is proposed for a class of infinite dimensional systems with bounded observation operators, where the disturbance is an unknown signal, and the solvability of the problem hinges on the solution to a corresponding operator equation, which yields exponential convergence of the state observation error to zero.
Journal ArticleDOI

A quantitative fault detection method for a class of nonlinear systems

TL;DR: In this paper, an observer-based fault detection method for a class of nonlinear models which have bilinear and quadratic nonlinear terms in their discrete state-space representations is proposed.
Journal ArticleDOI

An Integrated Fault Detection and Isolation and Safe-Parking Framework for Networked Process Systems

TL;DR: In this paper, the authors consider the problem of fault detection and isolation for networked process systems subject to actuator faults, where multiple units are interconnected in the context of multiple failures.
References
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Book

Linear System Theory and Design

TL;DR: Striking a balance between theory and applications, Linear System Theory and Design, 3/e, is ideal for use in advanced undergraduate/first-year graduate courses in linear systems and multivariable system design in electrical, mechanical, chemical, and aeronautical engineering departments.
Journal ArticleDOI

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

Paul M. Frank
- 01 May 1990 - 
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.