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Title: Adaptive control scheme based on the least squares support vector machine network

Autor:

Mahmoud, Tarek A.

Data wydania:

2011

Typ zasobu:

artykuł

Współtwórca:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Tytuł publikacji grupowej:

AMCS, Volume 21 (2011)

Abstract:

Recently, a new type of neural networks called Least Squares Support Vector Machines (LS-SVMs) has been receiving increasing attention in nonlinear system identification and control due to its generalization performance. This paper develops a stable adaptive control scheme using the LS-SVM network. The developed control scheme includes two parts: the identification part that uses a modified structure of LS-SVM neural networks called the multi-resolution wavelet least squares support vector machine network (MRWLS-SVM) as a predictor model, and the controller part that is developed to track a reference trajectory. By means of the Lyapunov stability criterion, stability analysis for the tracking errors is performed. Finally, simulation studies are performed to demonstrate the capability of the developed approach in controlling a pH process.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Identyfikator zasobu:

oai:zbc.uz.zgora.pl:46951

DOI:

10.2478/v10006-011-0054-6

Strony:

685-696

Źródło:

AMCS, Volume 21, Number 4 (2011) ; click here to follow the link

Jezyk:

eng

Licencja CC BY 4.0:

click here to follow the link

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego

Subject and keywords:

least squares support vector machine multi-resolution wavelet least squares support vector machine neural network nonlinear system modeling and control pH control

Object collections:

Last modified:

14 lip 2025

In our library since:

28 sie 2018

Number of object content hits:

322

All available object's versions:

https://zbc.uz.zgora.pl/repozytorium/publication/55052

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Adaptive control scheme based on the least squares support vector machine network 14 lip 2025

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