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Titlebook: Identification of Continuous-Time Systems; Methodology and Comp N. K. Sinha,G. P. Rao Book 1991 Springer Science+Business Media Dordrecht 1

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书目名称Identification of Continuous-Time Systems
副标题Methodology and Comp
编辑N. K. Sinha,G. P. Rao
视频video
丛书名称Intelligent Systems, Control and Automation: Science and Engineering
图书封面Titlebook: Identification of Continuous-Time Systems; Methodology and Comp N. K. Sinha,G. P. Rao Book 1991 Springer Science+Business Media Dordrecht 1
描述In view of the importance of system identification, the International Federation of Automatic Control (IFAC) and the International Federation of Operational Research Societies (IFORS) hold symposia on this topic every three years. Interest in continuous time approaches to system identification has been growing in recent years. This is evident from the fact that the of invited sessions on continuous time systems has increased from one in the 8th number Symposium that was held in Beijing in 1988 to three in the 9th Symposium in Budapest in 1991. It was during the 8th Symposium in August 1988 that the idea of bringing together important results on the topic of Identification of continuous time systems was conceived. Several distinguished colleagues, who were with us in Beijing at that time, encouraged us by promising on the spot to contribute to a comprehensive volume of collective work. Subsequently, we contacted colleagues all over the world, known for their work in this area, with a formal request to contribute to the proposed volume. The response was prompt and overwhelmingly encouraging. We sincerely thank all the authors for their valuable contributions covering various aspects
出版日期Book 1991
关键词Signal; computer; differential equation; model; modeling; orthogonal polynomials; system; system identifica
版次1
doihttps://doi.org/10.1007/978-94-011-3558-0
isbn_softcover978-94-010-5576-5
isbn_ebook978-94-011-3558-0Series ISSN 2213-8986 Series E-ISSN 2213-8994
issn_series 2213-8986
copyrightSpringer Science+Business Media Dordrecht 1991
The information of publication is updating

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SVD-based subspace methods for multivariable continuous-time systems identification,SVD), a numerical technique known to be very robust and accurate when dealing with noisy data. The noise coloring is compensated for by using a generalization of the SVD, namely the quotient SVD. The resulting identification scheme is then shown to give consistent results under certain conditions.
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Transformation of discrete-time models,t are already well established. Here, our emphasis is on transformations which will lead to a suitable continuous-time model from the identified discrete-time model. Several algorithms for such transformation are critically compared. Finally, a straightforward procedure for determining a continuous-time model from the δ-model is described.
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