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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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