Moving identification via weighted least-squares estimation

Wen Teng Wu; Y. T. Chu; Kuo Chieh Chen

doi:10.1080/00207728708963981

Moving identification via weighted least-squares estimation

Wen Teng Wu, Y. T. Chu, Kuo Chieh Chen

College of Engineering

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

Moving identification using weighted least-squares estimation is developed. Two weighting factors are used: one for discarding old data, the other for adding new data, and these two weighting factors are chosen to ensure that the estimated parameters are convergent. The sufficient conditions for the convergent property are also presented. The proposed method is suitable for time-varying systems.

Original language	English
Pages (from-to)	477-486
Number of pages	10
Journal	International Journal of Systems Science
Volume	18
Issue number	3
DOIs	https://doi.org/10.1080/00207728708963981
Publication status	Published - 1987

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Theoretical Computer Science
Computer Science Applications

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10.1080/00207728708963981

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title = "Moving identification via weighted least-squares estimation",

abstract = "Moving identification using weighted least-squares estimation is developed. Two weighting factors are used: one for discarding old data, the other for adding new data, and these two weighting factors are chosen to ensure that the estimated parameters are convergent. The sufficient conditions for the convergent property are also presented. The proposed method is suitable for time-varying systems.",

author = "Wu, {Wen Teng} and Chu, {Y. T.} and Chen, {Kuo Chieh}",

year = "1987",

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AU - Chu, Y. T.

AU - Chen, Kuo Chieh

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AB - Moving identification using weighted least-squares estimation is developed. Two weighting factors are used: one for discarding old data, the other for adding new data, and these two weighting factors are chosen to ensure that the estimated parameters are convergent. The sufficient conditions for the convergent property are also presented. The proposed method is suitable for time-varying systems.

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DO - 10.1080/00207728708963981

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JO - International Journal of Systems Science

JF - International Journal of Systems Science

SN - 0020-7721

IS - 3

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Moving identification via weighted least-squares estimation

Abstract

All Science Journal Classification (ASJC) codes

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