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A fault detection, identification, estimation and state estimation (FDIESE) problem involves joint decision and estimation (JDE). Decision contains detection and identification, while estimation is for fault severeness and system state. Both detection and identification are highly coupled with estimation and a fault is identified after detection. To solve this problem, an approach named nested joint...
This paper presents an approach to fault detection, identification, and state estimation (FDISE) for a dynamic system with abrupt total or partial failures. FDISE includes both decision and estimation and they are highly coupled. Decision includes fault detection and identification (FDI), while estimation is for failure magnitude and system state. Correct FDI benefits estimation and accurate estimation...
A polytopic model (PM) structure is often used in the areas of automatic control and fault detection as an alternative multiple model approach that explicitly allows for interpolation among local models. The model that is valid, usually unknown, is represented by a weighed combination of models in a given model set. Proposed is a novel approach to PM estimation by modeling the set of PM weights as...
In this paper we propose an approach to detect, identify and estimate failures, including partial failures, in a dynamic system. The approach (IM/sup 3/L) uses the interacting multiple model (IMM) estimators to detect and identify total and partial failures and the maximum likelihood estimator (MLE) to estimate the extent of failure. It provides an effective and integrated framework for fault detection,...
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