2017 American Control Conference (ACC) 2017
DOI: 10.23919/acc.2017.7963456
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A second order sliding mode differentiator with a variable exponent

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Cited by 14 publications
(16 citation statements)
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“…Many solutions are proposed to solve this issue, among them the high order sliding mode observers (HOSMO). Most HOSMO use the concept of homogeneity (see e.g., [28], [29], and [30]) based on the differentiation algorithms. In this context, Levant [31] proposed a robust exact differentiator.…”
Section: B Some Recalls On Observer Designmentioning
confidence: 99%
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“…Many solutions are proposed to solve this issue, among them the high order sliding mode observers (HOSMO). Most HOSMO use the concept of homogeneity (see e.g., [28], [29], and [30]) based on the differentiation algorithms. In this context, Levant [31] proposed a robust exact differentiator.…”
Section: B Some Recalls On Observer Designmentioning
confidence: 99%
“…It is well know that the super twisting differentiators [27] have good properties with respect to sensibility perturbation but their accuracy is degraded if the signal is perturbed by a noise, contrary to the linear observers that have good performances with respect to the measurement noise but they are sensible to perturbations. In [30], [33], a novel second order sliding mode differentiator with a variable exponent is proposed in order to make trade off between accuracy and noise sensibility. Following [30], [33], we explain the differentiator design, then, we will apply it to the electro-mechanical system.…”
Section: Observer Design Of the Electro-mechanical Systemmentioning
confidence: 99%
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“…The observers are used in order to control the behavior of systems, to detect the faults or to identify the unknown parameters of systems (Oueder 2012). In our case, four differentiatiors (Ghanes et al 2017) are used to estimate the drift of both currents of the asynchronous motor and the displacements of the gear element. Assuming that [s 1 , ..., s 8 ] = [i ds ,i ds , i qs ,i qs , θ 1 ,θ 1 , θ 2 ,θ 2 ], the observer equations are written in following form:…”
Section: Observer Formmentioning
confidence: 99%
“…Within this class of observers we recall passivity-based designs, e.g. [2]; techniques based on LMIs conditions, [5], [23], [25]; Luenberger-like observers (also known as Kazantzis-Kravaris Luenberger observers), e.g., [1], [13]; approaches which use normal forms induced by uniform observability conditions such as high-gain observers, e.g., [3], [4], [8], [14]; sliding-mode observers, e.g., [9]. When the system's dynamics are very complex, the design of such observers may be not possible, e.g., because of non-feasibility of the LMIs [2], [5], [25], or too complicated to apply, e.g.…”
Section: Introductionmentioning
confidence: 99%