Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/4687
Title: Online stabilization of chaotic maps via support vector machines based generalized predictive control
Authors: İplikçi, Serdar
Keywords: Computer simulation
Online systems
Perturbation techniques
Predictive control systems
Regression analysis
Vectors
Accurate Online Support Vector Regression (AOSVR) algorithm
Online stabilization
Support Vector Machines Based Generalized Predictive Control (SVM-Based GPC) approach
Chaos theory
Publisher: Springer Verlag
Abstract: In this study, the previously proposed Online Support Vector Machines Based Generalized Predictive Control method [1] is applied to the problem of stabilizing discrete-time chaotic systems with small parameter perturbations. The method combines the Accurate Online Support Vector Regression (AOSVR) algorithm [2] with the Support Vector Machines Based Generalized Predictive Control (SVM-Based GPC) approach [3] and thus provides a powerful scheme for controlling chaotic maps in an adaptive manner. The simulation results on chaotic maps have revealed that Online SVM-Based GPC provides an excellent online stabilization performance and maintains it when some measurement noise is added to output of the underlying map. © Springer-Verlag Berlin Heidelberg 2006.
URI: https://hdl.handle.net/11499/4687
ISBN: 03029743 (ISSN)
3540386254
9783540386254
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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