Generalized self-tuning regulator based on online support vector regression

This paper introduces a novel generalized self-tuning regulator based on online support vector regression (OSVR) for nonlinear systems. The main idea is to approximate the parameters of an adaptive controller by optimizing the regression margin between reference input and system output. For this pur...

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Veröffentlicht in:	Neural computing & applications 2017-12, Vol.28 (Suppl 1), p.775-801
Hauptverfasser:	Uçak, Kemal, Günel, Gülay Öke
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive control Architecture Artificial Intelligence Bioreactors Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer simulation Data Mining and Knowledge Discovery Fuzzy control Image Processing and Computer Vision Mathematical models Nonlinear systems Operating systems Optimization Original Article Probability and Statistics in Computer Science Proportional integral derivative Regression Self tuning Support vector machines Tracking
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