2013
DOI: 10.1016/j.jfranklin.2012.04.008
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Observer design for a class of nonlinear descriptor systems

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Cited by 20 publications
(11 citation statements)
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“…Then, by replacing Z with F X R 0 S Â Ã in Eq. (15), straightforward calculation leads to the condition (14) associated with the close-loop system (8). Hence, the closed-loop system (8) is admissible and its transfer function from w(k) to y(k) is ESPR.…”
Section: Corollarymentioning
confidence: 99%
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“…Then, by replacing Z with F X R 0 S Â Ã in Eq. (15), straightforward calculation leads to the condition (14) associated with the close-loop system (8). Hence, the closed-loop system (8) is admissible and its transfer function from w(k) to y(k) is ESPR.…”
Section: Corollarymentioning
confidence: 99%
“…Conversely, if Problem 1 is solvable, then the condition (14) holds for the closed-loop system (8). Using the linear change of variables F X…”
Section: Corollarymentioning
confidence: 99%
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“…In this context, many methods have been developed as for instance observer-based approaches [1][2][3][4], identification-based methods [5,6], fuzzy logic-based approaches [7][8][9][10] and neural-network-based methods [11,12]. The effectiveness of these approaches for detecting and diagnosing certain types of system faults, which can take the form of sensor faults, actuator faults or process faults, was demonstrated in several application cases [13,14]. Among the model-based FDD methods, the observer-based method plays an important role, in which the key issue is to select suitable diagnostic observer parameters and design a fault estimation rule so that the observation error system is asymptotically stable and the estimated faults approach their true values.…”
Section: Introductionmentioning
confidence: 99%
“…Many publications deal with nonlinear descriptor systems which can be described by a linear one disturbed by some nonlinearity (see e.g. [10,11,15,22,23,27,33,35,36,38,39]). If the nonlinearity satisfies a local Lipschitz condition, it is compensated and the design is carried on with linear methods.…”
Section: Introductionmentioning
confidence: 99%