Abstract
A Least-Squares Support Vector Machine (LS-SVM) estimator, formulated in the frequency domain is proposed to identify linear time-varying dynamic systems. The LS-SVM aims at learning the structure of the time variation in a data driven way. The frequency domain is chosen for its superior robustness w.r.t. correlated errors for the calibration of the hyper parameters of the model.
The time-domain and the frequency-domain implementations are compared on a simulation example to show the effectiveness of the proposed approach. It is demonstrated that the time- domain formulation is mislead during the calibration due to the fact that the noise on the estimation and calibration data sets are correlated. This is not the case for the frequency-domain implementation.
Original language | English |
---|---|
Title of host publication | Proceedings of the 19th IFAC World Congress of the International Federation of Automatic Control, (IFAC'14), 24-29 August 2014, Cape Town, South Africa |
Pages | 10024-10029 |
Publication status | Published - 2014 |
Event | 19th World Congress of the International Federation of Automatic Control (IFAC 2014 World Congress) - Cape Town International Convention Centre, Cape Town, South Africa Duration: 24 Aug 2014 → 29 Aug 2014 Conference number: 19 http://www.ifac2014.org |
Conference
Conference | 19th World Congress of the International Federation of Automatic Control (IFAC 2014 World Congress) |
---|---|
Abbreviated title | IFAC 2014 |
Country/Territory | South Africa |
City | Cape Town |
Period | 24/08/14 → 29/08/14 |
Internet address |