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Identification of Continuous-Time Systems - Linear and Robust Parameter Estimation (Hardcover) Loot Price: R3,421
Discovery Miles 34 210
Identification of Continuous-Time Systems - Linear and Robust Parameter Estimation (Hardcover): Allamaraju Subrahmanyam, Ganti...

Identification of Continuous-Time Systems - Linear and Robust Parameter Estimation (Hardcover)

Allamaraju Subrahmanyam, Ganti Prasada Rao

Series: Engineering Systems and Sustainability

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Loot Price R3,421 Discovery Miles 34 210 | Repayment Terms: R321 pm x 12*

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Models of dynamical systems are required for various purposes in the field of systems and control. The models are handled either in discrete time (DT) or in continuous time (CT). Physical systems give rise to models only in CT because they are based on physical laws which are invariably in CT. In system identification, indirect methods provide DT models which are then converted into CT. Methods of directly identifying CT models are preferred to the indirect methods for various reasons. The direct methods involve a primary stage of signal processing, followed by a secondary stage of parameter estimation. In the primary stage, the measured signals are processed by a general linear dynamic operation-computational or realized through prefilters, to preserve the system parameters in their native CT form-and the literature is rich on this aspect. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation. In this book, the authors provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification, bring them into mainstream model parameterization via basis functions, present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models, suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and indicate some directions for further research. This modest volume is intended to be a useful addition to the literature on identifying CT systems.

General

Imprint: Crc Press
Country of origin: United Kingdom
Series: Engineering Systems and Sustainability
Release date: December 2019
First published: 2020
Authors: Allamaraju Subrahmanyam • Ganti Prasada Rao
Dimensions: 234 x 156 x 15mm (L x W x T)
Format: Hardcover
Pages: 120
ISBN-13: 978-0-367-37143-2
Categories: Books > Science & Mathematics > Mathematics > General
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
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LSN: 0-367-37143-X
Barcode: 9780367371432

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