Multiscale fuzzy state estimation using stationary wavelet transforms

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Multiscale representation of data is a powerful data analysis tool, which has been successfully used to solve several data filtering problems. For nonlinear systems, which can be represented by a Takagi-Sugeno fuzzy model, several Fuzzy Kalman filtering algorithms have been developed to extend Kalman filtering for such systems. In this paper, a multiscale Fuzzy Kalman (MSFK) filtering algorithm, in which multiscale representation is utilized to improve the performance of Fuzzy Kalman filtering, is developed. The idea is to apply fuzzy Kalman filtering at multiple scales to combine its advantages with those of the low pass filters used in multiscale data representation. Starting with a fuzzy model in the time domain, a similar fuzzy model is derived at each scale using the scaled signal approximation of the data obtained by stationary wavelet transform (SWT). These multiscale fuzzy models are then used in fuzzy Kalman filtering, and the fuzzy Kalman filter with the least cross validation mean square error among all scales is selected as the optimum filter. Finally, the performance of the developed MSFK filtering algorithm is illustrated through a simulated example.

Original languageEnglish
Title of host publicationProceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
Pages3249-3254
Number of pages6
Volume2005
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 - Seville, Spain
Duration: 12 Dec 200515 Dec 2005

Other

Other44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
CountrySpain
CitySeville
Period12/12/0515/12/05

Fingerprint

State estimation
Wavelet transforms
Low pass filters
Kalman filters
Mean square error
Nonlinear systems

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Nounou, H. (2005). Multiscale fuzzy state estimation using stationary wavelet transforms. In Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 (Vol. 2005, pp. 3249-3254). [1582662] https://doi.org/10.1109/CDC.2005.1582662

Multiscale fuzzy state estimation using stationary wavelet transforms. / Nounou, Hazem.

Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05. Vol. 2005 2005. p. 3249-3254 1582662.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nounou, H 2005, Multiscale fuzzy state estimation using stationary wavelet transforms. in Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05. vol. 2005, 1582662, pp. 3249-3254, 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05, Seville, Spain, 12/12/05. https://doi.org/10.1109/CDC.2005.1582662
Nounou H. Multiscale fuzzy state estimation using stationary wavelet transforms. In Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05. Vol. 2005. 2005. p. 3249-3254. 1582662 https://doi.org/10.1109/CDC.2005.1582662
Nounou, Hazem. / Multiscale fuzzy state estimation using stationary wavelet transforms. Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05. Vol. 2005 2005. pp. 3249-3254
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