On-line nonparametric regression to learn state-dependent disturbances


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Kruif, Bas J. de and Vries, Theo J.A. de (2003) On-line nonparametric regression to learn state-dependent disturbances. In: IEEE International Symposium on Intelligent Control, 2003, October 5-8, 2003, Houston, Texas (pp. pp. 75-80).

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Abstract:A combination of recursive least squares and weighted least squares is made which can adapt its structure such that a relation between in- and output can he approximated, even when the structure of this relation is unknown beforehand.
This method can adapt its structure on-line while it preserves information offered by previous samples, making it applicable in a control setting. This method has been tested with compntergenerated data, and it b used in a simulation to learn the non-linear state-dependent effects, both with good success.
Item Type:Conference or Workshop Item
Copyright:© 2003 IEEE
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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Link to this item:http://purl.utwente.nl/publications/74467
Official URL:http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1253917
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