Failure Detection with Uncertain Models

Lou, Xi-Cheng; Willsky, Alan S.; Verghese, George C.

doi:10.23919/acc.1983.4788254

Cited by 8 publications

(5 citation statements)

References 7 publications

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“…We are aware that any model-based diagnostic scheme such as this one has to deal with the issue of robustness [IO,11,4]. We m currently looking into this issue in the context of multirate systems.…”

mentioning

confidence: 99%

Fault diagnosis in multirate sampled data systems

Viswanadham

Minto

1990

29th IEEE Conference on Decision and Control

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In this paper we present three new schemes for sensor and actuator fault diagnosis for linear time-invariant systems: multirate parity-space techniques, multirate observers, and multirate detection filters. We show that these approaches offer distinct advantages over conventional fault diagnosis schemes in terms of ease of failure detection, the speed and the class of systems for which detection is possible.There are two primary contributions in this paper. First, we develop schemes for system-wide fault diagnosis, as compared with single component fault detection and isolation. Secondly, we show that the diagnosis of single faults is a generic system property.

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mentioning

confidence: 99%

Fault diagnosis in multirate sampled data systems

Viswanadham

Minto

1990

29th IEEE Conference on Decision and Control

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“…However, we will focus for the most part on the first task of change detection, that is, the problem of producing signals which make subsequent detection as easy as possible. As discussed here and in more detail in [27][28][29], this is an exceedingly important perspective in the design of detection methods which are robust to uncertain details of the dynamic models on which they are based.…”

Section: Introductionmentioning

confidence: 99%

“…These efforts have been motivated by a wide variety of applications including the detection of sensor and actuator failures [1,2,4,19,[26][27][28][29][30][31][32][33][34][35] the tracking of maneuvering vehicles [20,21,23,25], and numerous signal analysis problems (electrocardiogram analysis [5,6], geophysical signal processing [7], edge detection in images [8,9], freeway monitoring [10,11],...).…”

Section: Introductionmentioning

confidence: 99%

Detection of abrupt changes in dynamic systems

Willsky

Detection of Abrupt Changes in Signals and Dynamical Systems

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In this paper we present some of the basic ideas associated with the detection of abrupt changes in dynamic systems. Our presentation focuses on two classes of methods --multiple filter-based techniques and residual-based methods --and in far more detail on the multiple model and generalized likelihood ratio methods. Issues such as the effect of unknown onset time on algorithm complexity and structure and robustness to model uncertainty are discussed.

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“…In [2] we present one criterion for measuring the reliability of a particular redundancy relation and use this to pose an optimization problem to determine the most reliable relation. In [3,19] we present another method which has some computational advantages not found -3-in the approach described in [2].…”

Section: Introductionmentioning

confidence: 99%

“…In this paper we describe the major results of [2,3,19]. In the next section we review the notion of analytic redundancy for perfectly known models and provide a geometric interpretation which forms the starting point for our investigation of robust failure detection.…”

Section: Introductionmentioning

confidence: 99%

Redundancy relations and robust failure detection

Chow

Lou

Verghese

et al.

Detection of Abrupt Changes in Signals and Dynamical Systems

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All failure detection methods are based on the use of redundancy, that is on (possible dynamic) relations among the measured variables.Consequently the robustness of the failure detection process depends to a great degree on the reliability of the redundancy relations given the inevitable presence of model uncertainties.In this paper we address the problem of determining redundancy relations which are optimally robust in a sense which includes the major issues of importance in practical failure detection and which provides us with a significant amount of intuition concerning the geometry of robust failure detection.

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Failure Detection with Uncertain Models

Cited by 8 publications

References 7 publications

Fault diagnosis in multirate sampled data systems

Fault diagnosis in multirate sampled data systems

Detection of abrupt changes in dynamic systems

Redundancy relations and robust failure detection

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