Zobrazeno 1 - 9
of 9
pro vyhledávání: '"M. N. Abdelkrim"'
Publikováno v:
Actuators, Vol 13, Iss 7, p 253 (2024)
Synchronizing a network of robots in consensus is an important task for cooperative work. Detecting faults in a network of robots in consensus is a much more important task. In considering a formation of Wheeled Mobile Robots (WMRs) in a master–sla
Externí odkaz:
https://doaj.org/article/e65581bdaa104019b5ceb042115d5c33
Publikováno v:
Automatika, Vol 59, Iss 1, Pp 104-119 (2018)
This work deals with a physical one- and two-dimensional (1D and 2D) parameters estimation of a filtration process of slurry, the second stage of phosphoric acid manufacture. This study focuses on recursive least square and instrumental variable tech
Externí odkaz:
https://doaj.org/article/0dcab8adc29f48f8a49a60992ca83c0f
Autor:
Morched Derbali, Seyed M. Buhari, Georgios Tsaramirsis, Milos Stojmenovic, H. Jerbi, M. N. Abdelkrim, Mohammad H. Al-Beirutty
Publikováno v:
IEEE Access, Vol 5, Pp 23266-23275 (2017)
The presence of faulty valves has been studied in the literature with various machine learning approaches. The impact of using fault data only to train the system could solve the class imbalance problem in the machine learning approach. The data sets
Externí odkaz:
https://doaj.org/article/b2eee48615da466b820a00aeda21f527
Autor:
Yemna Bensalem, Abelkader Abbassi, Rabeh Abbassi, Houssem Jerbi, Mansoor Alturki, Abdullah Albaker, Abdallah Kouzou, M. N. Abdelkrim
Publikováno v:
Electrical Engineering. 104:2155-2171
This paper investigates a method for the state estimation of nonlinear systems described by a class of differential-algebraic equation (DAE) models using the extended Kalman filter. The method involves the use of a transformation from a DAE to ordina
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::510e3f44d5d62504811080530983732f
Publikováno v:
AIP Conference Proceedings.
This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quo
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Conference
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