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

Creator:

Mahmoud, Tarek A.

Date:

2011

Resource Type:

artykuł

Contributor:

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

Group publication title:

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.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Resource Identifier:

oai:zbc.uz.zgora.pl:46951

DOI:

10.2478/v10006-011-0054-6

Pages:

685-696

Source:

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

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

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:

Jul 14, 2025

In our library since:

Aug 28, 2018

Number of object content hits:

280

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 Jul 14, 2025

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