Detection filter design: Spectral theory and algorithms

White, John H.; Speyer, Jason L.

doi:10.1109/tac.1987.1104682

Cited by 352 publications

(35 citation statements)

References 5 publications

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“…It was first developed by Beard [28] and [29] and later revisited by Massoumnia [30] in the geometric framework and by White and Speyer [31] and Park and Rizzoni [32] in the context of eigenstructure assignment. Further improvements were suggested by Liu and Si [33], and Keller [27].…”

Section: Modified Fault Isolation Filtermentioning

confidence: 99%

Fault Isolation Filter for Networked Control System with Event-Triggered Sampling Scheme

Sauter

2011

Sensors

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In this paper, the sensor data is transmitted only when the absolute value of difference between the current sensor value and the previously transmitted one is greater than the given threshold value. Based on this send-on-delta scheme which is one of the event-triggered sampling strategies, a modified fault isolation filter for a discrete-time networked control system with multiple faults is then implemented by a particular form of the Kalman filter. The proposed fault isolation filter improves the resource utilization with graceful fault estimation performance degradation. An illustrative example is given to show the efficiency of the proposed method.

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Section: Modified Fault Isolation Filtermentioning

confidence: 99%

Fault Isolation Filter for Networked Control System with Event-Triggered Sampling Scheme

Sauter

2011

Sensors

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“…Under the method considered, D is chosen in such a way that in case of failure in the system the residuals e, e = y -C i , should be observed in that direction which is determined by the type of the failure (White and Speyer 1987).…”

Section: Fd With Deteetor Filtermentioning

confidence: 99%

“…n, give the failure directions and let 11: = Chi. In such a case the detector filter satisfies the following equations (White and Speyer 1987):…”

Section: Rerltetdancy Of Operarionmentioning

confidence: 99%

Informational basis of the functional diagnostics of dynamic systems

Stefanov

1991

Int. J. of Systems Sc.

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The informational basis of the functional diagnostics of linear dynamic systems is presented. For this purpose three laws of operation of such systems are formulated. These are laws of entropy or entropy production minimization by a system in case of failure. The laws have been obtained by defining the operation redundancy and the equations about that redundancy or its production. Methods for functional diagnostics of linear dynamic systems, covering all possible types of operation redundancy, are considered. The methods for functional diagnostics of linear dynamic systems are classified by means of the operation redundancy.

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“…The patient mortality by 45% if the glucose level is kept less palette of the detection filter design is large (Massoumnia, than 6.1 mmol/L for a cardiac care population. It was shown 1986; White and Speyer, 1987;Bassville, 1998).…”

Section: Introductionmentioning

confidence: 97%

LPV fault detection of glucose-insulin system

Kovács

Kulcsár

Bokor

et al. 2006

2006 14th Mediterranean Conference on Control and Automation

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A new approach is proposed in the paper for un-that automated control algorithms capable of tight regulation known glucose inlet estimation in case of diabetic patients under for glucose intolerant ICU patients would reduce mortality, insensitive care in form of a Linear Parameter Varying (LPV) as well the current burden on ICU medical resources and model class. The nonlinear two compartment glucose-insulin time system is rewritten in affine parameter varying form in order des to handle the dynamics with LPV Fault Detection and IsolationTo design an appropriate control, an adequate model is (FDI) method. The aim of the closed-loop fault detection, on necessary. In the last 50 years, a variety of models for the the one hand, is to estimate the unknown disturbance input interaction between glucose and insulin have been suggested.of the system, on the other hand to recognize the actuator However, the simplest model proved to be the minimal fault. A parameter varying controller assures the performance model of (Bergman et al., 1979), but its shortcoming is its requirements and stability Of the system.FDquiremeLPV,a csebinliny system, big sensitivity to variance in the parameters and that the Problem inVRecsle-neaion plasma insulin concentration must be known as a function Problem in Residual Generation of time. Therefore, extensions of this minimal model have

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Detection filter design: Spectral theory and algorithms

Cited by 352 publications

References 5 publications

Fault Isolation Filter for Networked Control System with Event-Triggered Sampling Scheme

Fault Isolation Filter for Networked Control System with Event-Triggered Sampling Scheme

Informational basis of the functional diagnostics of dynamic systems

LPV fault detection of glucose-insulin system

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