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Model Reference Control Based on SVM

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Advances in Neural Networks - ISNN 2004 (ISNN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3174))

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Abstract

A model reference control algorithm based on Support Vector Machine (SVM) for discrete nonlinear systems is proposed in this article. It uses SVM as regression tools to learn the feed forward controller from input and output data. Further more, a compensator is used as the feed back controller to make the whole system more robust. Advantages of SVM and the robust compensator help the method perform excellently as shown in the experiments.

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© 2004 Springer-Verlag Berlin Heidelberg

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He, J., Zhang, Z. (2004). Model Reference Control Based on SVM. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_21

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  • DOI: https://doi.org/10.1007/978-3-540-28648-6_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22843-1

  • Online ISBN: 978-3-540-28648-6

  • eBook Packages: Springer Book Archive

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