2009
DOI: 10.1109/tr.2009.2019496
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A Generalized Fault Coverage Model for Linear Time-Invariant Systems

Abstract: This paper proposes a fault coverage model for Linear Time-Invariant (LTI) systems subject to uncertain input. A state-space representation, defined by the state-transition matrix, and the input matrix, is used to represent LTI system dynamic behavior. The uncertain input is considered to be unknown but bounded, where the bound is defined by an ellipsoid. The state-transition matrix, and the input matrix must be such that, for any possible input, the system dynamics meets its intended function, which can be de… Show more

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Cited by 10 publications
(7 citation statements)
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“…It is defined as the conditional probability that, given a fault has occurred, the system architecture is altered, and the intended functionality is restored [51]. Techniques to quantify fault coverage for dynamical systems of the kind considered in this paper are proposed in [52]. In essence, if detailed models are available, the FDIR effectiveness to handle each particular fault can be quantified by fault coverage c, which can be incorporated into the state-transition diagram, as shown in Fig.…”
Section: A Preliminariesmentioning
confidence: 99%
See 1 more Smart Citation
“…It is defined as the conditional probability that, given a fault has occurred, the system architecture is altered, and the intended functionality is restored [51]. Techniques to quantify fault coverage for dynamical systems of the kind considered in this paper are proposed in [52]. In essence, if detailed models are available, the FDIR effectiveness to handle each particular fault can be quantified by fault coverage c, which can be incorporated into the state-transition diagram, as shown in Fig.…”
Section: A Preliminariesmentioning
confidence: 99%
“…As a consequence of a fault in State 1, a transition may be made to State 2 (fault detected and isolated) or to State 3 (failed state). Design and implementation aspects of FDIR are beyond the scope of this paper, and readers are referred to [50] and [52] and the references within for further information. In this study, we assume perfect FDIR, which implies c = 1.…”
Section: A Preliminariesmentioning
confidence: 99%
“…The parameter vector can be expressed as where is the vector of nominal parameter values, and where is a parallelotope defined as (6) The vertices of are determined by the parameter value ranges, while the vectors define the edges of [14]. Given this unknown-but-bounded parametric uncertainty model, we are interested in characterizing the uncertainty in the stationary distribution .…”
Section: B Problem Statementmentioning
confidence: 99%
“…This assumption can be validated by two facts. The first is that the attack rate on control systems is often lower than the one on information systems, [17], and the second one is that the time scale of the failure rate of devices and components in control systems is larger than the one of the system dynamics and operations [18].…”
Section: A Control Frameworkmentioning
confidence: 99%