2016
DOI: 10.1016/j.conengprac.2016.09.004
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Reduced-order hybrid interval observer for verified state estimation of an induction machine

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Cited by 18 publications
(22 citation statements)
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“…Therefore, reduced-order interval observers do have certain advantages in the area of interval estimation. To be specific, [27] adopts a reduced-order interval observer method to estimate the states of an induction machine system which is time-variant and gets excellent interval estimation results.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, reduced-order interval observers do have certain advantages in the area of interval estimation. To be specific, [27] adopts a reduced-order interval observer method to estimate the states of an induction machine system which is time-variant and gets excellent interval estimation results.…”
Section: Introductionmentioning
confidence: 99%
“…then, the interval functional error (24) is Input-to-State Stable for any switching signal with the average dwell time (12),…”
Section: Resultsmentioning
confidence: 99%
“…Thus, the design of functional interval observers [17] that reconstruct directly an upper and a lower bounds of a linear function of the state is of a great importance. In [12] and [2] reduced interval observers have been proposed for linear time-variant 1 All authors are with IBISC Laboratory, Univ Evry, Paris-Saclay university, Evry, 91020, France. E-mail: {sara.ifqir, dalil.ichalal, naima.aitoufroukh, said.mammar} @univ-evry.fr and linear time-delay systems.…”
Section: Introductionmentioning
confidence: 99%
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“…However, approaches like the extended Luenberger Observer, the extended Kalman Filter, the High-Gain Observer, the Sliding Mode Observer, the Observer, or the -Gain Observer are not directly applicable with a priori assumptions on probability distributions or models of the uncertainties, because these are often unknown for practical applications. Furthermore, such methods, e.g., Sun et al [ 9 ], cannot be used because they do not provide necessary guaranteed error bounds [ 10 ]. Therefore, it is reasonable to utilize methods that assume that the uncertainties are unknown but their boundaries are specified, which is usually given for practical applications.…”
Section: Motivation and Overviewmentioning
confidence: 99%