國立虎尾科技大學 |

Errors-in-Variables Methods in System Identification

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Errors-in-Variables Methods in System Identification/ by Torsten Söderström.
Author:	Söderström, Torsten.
Description:	XXVII, 485 p. 30 illus., 3 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Control engineering. -
Online resource:	https://doi.org/10.1007/978-3-319-75001-9
ISBN:	9783319750019

Errors-in-Variables Methods in System Identification
Söderström, Torsten.

Errors-in-Variables Methods in System Identification[electronic resource] /by Torsten Söderström. - 1st ed. 2018. - XXVII, 485 p. 30 illus., 3 illus. in color.online resource. - Communications and Control Engineering,0178-5354. - Communications and Control Engineering,.

Chapter 1. Introduction -- Chapter 2. The Static Case -- Chapter 3. The Errors-in-Variables Problem for Dynamic Systems -- Chapter 4. Identiﬁability Aspects -- Chapter 5. Modeling Aspects -- Chapter 6. Elementary Methods -- Chapter 7. Methods Based on Bias-Compensation -- Chapter 8. Covariance Matching -- Chapter 9. Prediction Error and Maximum Likelihood Methods -- Chapter 10. Frequency Domain Methods -- Chapter 11. Total Least Squares -- Chapter 12. Methods for Periodic Data -- Chapter 13. Algorithmic Properties -- Chapter 14. Asymptotic Distributions -- Chapter 15. Errors-in-Variables Problems in Practice -- Index -- References.

This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems. .

ISBN: 9783319750019

Standard No.: 10.1007/978-3-319-75001-9doiSubjects--Topical Terms:

1249728
Control engineering.

LC Class. No.: TJ212-225

Dewey Class. No.: 629.8

Errors-in-Variables Methods in System Identification
LDR:04205nam a22004095i 4500 001 991706
003 DE-He213
005 20200704193807.0
007 cr nn 008mamaa
008 201225s2018 gw | s |||| 0|eng d
020 $a 9783319750019 $9 978-3-319-75001-9
024 7 $a 10.1007/978-3-319-75001-9 $2 doi
035 $a 978-3-319-75001-9
050 4 $a TJ212-225
072 7 $a TJFM $2 bicssc
072 7 $a TEC004000 $2 bisacsh
072 7 $a TJFM $2 thema
082 0 4 $a 629.8 $2 23
100 1 $a Söderström, Torsten. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1283379
245 1 0 $a Errors-in-Variables Methods in System Identification $h [electronic resource] / $c by Torsten Söderström.
250 $a 1st ed. 2018.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a XXVII, 485 p. 30 illus., 3 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Communications and Control Engineering, $x 0178-5354
505 0 $a Chapter 1. Introduction -- Chapter 2. The Static Case -- Chapter 3. The Errors-in-Variables Problem for Dynamic Systems -- Chapter 4. Identiﬁability Aspects -- Chapter 5. Modeling Aspects -- Chapter 6. Elementary Methods -- Chapter 7. Methods Based on Bias-Compensation -- Chapter 8. Covariance Matching -- Chapter 9. Prediction Error and Maximum Likelihood Methods -- Chapter 10. Frequency Domain Methods -- Chapter 11. Total Least Squares -- Chapter 12. Methods for Periodic Data -- Chapter 13. Algorithmic Properties -- Chapter 14. Asymptotic Distributions -- Chapter 15. Errors-in-Variables Problems in Practice -- Index -- References.
520 $a This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems. .
650 0 $a Control engineering. $3 1249728
650 0 $a System theory. $3 566168
650 0 $a Electrical engineering. $3 596380
650 0 $a Computer communication systems. $3 1115394
650 0 $a Statistics . $3 1253516
650 1 4 $a Control and Systems Theory. $3 1211358
650 2 4 $a Systems Theory, Control. $3 669337
650 2 4 $a Communications Engineering, Networks. $3 669809
650 2 4 $a Computer Communication Networks. $3 669310
650 2 4 $a Statistical Theory and Methods. $3 671396
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319750002
776 0 8 $i Printed edition: $z 9783319750026
776 0 8 $i Printed edition: $z 9783030091255
830 0 $a Communications and Control Engineering, $x 0178-5354 $3 1254247
856 4 0 $u https://doi.org/10.1007/978-3-319-75001-9
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)