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An adaptive derivative estimator for fault-detection Using a dynamic system with a suboptimal parameter

Research output: Journal contributions › Journal articles › Research › peer-review

Standard

An adaptive derivative estimator for fault-detection Using a dynamic system with a suboptimal parameter. / Schimmack, Manuel; Mercorelli, Paolo.
In: Algorithms, Vol. 12, No. 5, 101, 10.05.2019.

Research output: Journal contributions › Journal articles › Research › peer-review

Harvard

Schimmack, M & Mercorelli, P 2019, 'An adaptive derivative estimator for fault-detection Using a dynamic system with a suboptimal parameter', Algorithms, vol. 12, no. 5, 101. https://doi.org/10.3390/a12050101

APA

Schimmack, M., & Mercorelli, P. (2019). An adaptive derivative estimator for fault-detection Using a dynamic system with a suboptimal parameter. Algorithms, 12(5), Article 101. https://doi.org/10.3390/a12050101

Vancouver

Schimmack M, Mercorelli P. An adaptive derivative estimator for fault-detection Using a dynamic system with a suboptimal parameter. Algorithms. 2019 May 10;12(5):101. doi: 10.3390/a12050101

Bibtex

@article{b9a377f1d3634328bc503d0fb257fd7f,
title = "An adaptive derivative estimator for fault-detection Using a dynamic system with a suboptimal parameter",
abstract = "This paper deals with an approximation of a first derivative of a signal using a dynamic system of the first order. After formulating the problem, a proposition and a theorem are proven for a possible approximation structure, which consists of a dynamic system. In particular, a proposition based on a Lyapunov approach is proven to show the convergence of the approximation. The proven theorem is a constructive one and shows directly the suboptimality condition in the presence of noise. Based on these two results, an adaptive algorithm is conceived to calculate the derivative of a signal with convergence in infinite time. Results are compared with an approximation of the derivative using an adaptive Kalman filter (KF).",
keywords = "Derivative approximation, Estimator, Least squares method, Lyapunov approach, Engineering",
author = "Manuel Schimmack and Paolo Mercorelli",
year = "2019",
month = may,
day = "10",
doi = "10.3390/a12050101",
language = "English",
volume = "12",
journal = "Algorithms",
issn = "1999-4893",
publisher = "MDPI AG",
number = "5",

}

RIS

TY - JOUR

T1 - An adaptive derivative estimator for fault-detection Using a dynamic system with a suboptimal parameter

AU - Schimmack, Manuel

AU - Mercorelli, Paolo

PY - 2019/5/10

Y1 - 2019/5/10

N2 - This paper deals with an approximation of a first derivative of a signal using a dynamic system of the first order. After formulating the problem, a proposition and a theorem are proven for a possible approximation structure, which consists of a dynamic system. In particular, a proposition based on a Lyapunov approach is proven to show the convergence of the approximation. The proven theorem is a constructive one and shows directly the suboptimality condition in the presence of noise. Based on these two results, an adaptive algorithm is conceived to calculate the derivative of a signal with convergence in infinite time. Results are compared with an approximation of the derivative using an adaptive Kalman filter (KF).

AB - This paper deals with an approximation of a first derivative of a signal using a dynamic system of the first order. After formulating the problem, a proposition and a theorem are proven for a possible approximation structure, which consists of a dynamic system. In particular, a proposition based on a Lyapunov approach is proven to show the convergence of the approximation. The proven theorem is a constructive one and shows directly the suboptimality condition in the presence of noise. Based on these two results, an adaptive algorithm is conceived to calculate the derivative of a signal with convergence in infinite time. Results are compared with an approximation of the derivative using an adaptive Kalman filter (KF).

KW - Derivative approximation

KW - Estimator

KW - Least squares method

KW - Lyapunov approach

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85066603842&partnerID=8YFLogxK

U2 - 10.3390/a12050101

DO - 10.3390/a12050101

M3 - Journal articles

AN - SCOPUS:85066603842

VL - 12

JO - Algorithms

JF - Algorithms

SN - 1999-4893

IS - 5

M1 - 101

ER -

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Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

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