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Subspace Identification for Linear Systems

Name: Subspace Identification for Linear Systems
Brand: Springer-Verlag New York Inc.
SKU: 9781461380610
Price: 53915 HUF
Availability: InStock

Theory Implementation Applications

Szerző: Peter van Overschee, B.L. de Moor

Nyelv:

Kötés: Puha kötésű

Kiadó: Springer-Verlag New York Inc.

Elérhetőség: Beszállítói készleten

Küldés 5-8 napon belül

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Subspace Identification for Linear Systems focuses on the theory, implementation and applications of...

Információk a könyvről

Szerző

Peter van Overschee, B.L. de Moor

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2011

oldal

272

EAN

9781461380610

ISBN

1461380618

Enbook ID

06797148

Kiadó

Springer-Verlag New York Inc.

Súly

392

Méretek

158 x 235 x 15

Teljes leírás

Subspace Identification for Linear Systems focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finite- dimensional dynamical systems. These algorithms allow for a fast, straightforward and accurate determination of linear multivariable models from measured input-output data.§The theory of subspace identification algorithms is presented in detail. Several chapters are devoted to deterministic, stochastic and combined deterministic-stochastic subspace identification algorithms. For each case, the geometric properties are stated in a main 'subspace' Theorem. Relations to existing algorithms and literature are explored, as are the interconnections between different subspace algorithms. The subspace identification theory is linked to the theory of frequency weighted model reduction, which leads to new interpretations and insights. §The implementation of subspace identification algorithms is discussed in terms of the robust and computationally efficient RQ and singular value decompositions, which are well-established algorithms from numerical linear algebra. The algorithms are implemented in combination with a whole set of classical identification algorithms, processing and validation tools in Xmath's ISID, a commercially available graphical user interface toolbox. The basic subspace algorithms in the book are also implemented in a set of Matlab files accompanying the book. §An application of ISID to an industrial glass tube manufacturing process is presented in detail, illustrating the power and user-friendliness of the subspace identification algorithms and of their implementation in ISID. The identified model allows for an optimal control of the process, leading to a significant enhancement of the production quality. The applicability of subspace identification algorithms in industry is further illustrated with the application of the Matlab files to ten practical problems. Since all necessary data and Matlab files are included, the reader can easily step through these applications, and thus get more insight in the algorithms. §Subspace Identification for Linear Systems is an important reference for all researchers in system theory, control theory, signal processing, automization, mechatronics, chemical, electrical, mechanical and aeronautical engineering.