System Identification and Adaptive Control (Record no. 57930)

000 -LEADER
fixed length control field 05026nam a22005655i 4500
001 - CONTROL NUMBER
control field 978-3-319-06364-5
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112230.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140422s2014 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319063645
-- 978-3-319-06364-5
082 04 - CLASSIFICATION NUMBER
Call Number 629.8
100 1# - AUTHOR NAME
Author Boutalis, Yiannis.
245 10 - TITLE STATEMENT
Title System Identification and Adaptive Control
Sub Title Theory and Applications of the Neurofuzzy and Fuzzy Cognitive Network Models /
300 ## - PHYSICAL DESCRIPTION
Number of Pages XII, 313 p. 120 illus., 56 illus. in color.
490 1# - SERIES STATEMENT
Series statement Advances in Industrial Control,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Part I The Recurrent Neurofuzzy Model -- Introduction and Scope -- Identification of Dynamical Systems Using Recurrent Neurofuzzy Modeling -- Indirect Adaptive Control Based on the Recurrent Neurofuzzy Model -- Direct Adaptive Neurofuzzy Control of SISO Systems -- Direct Adaptive Neurofuzzy Control of MIMO Systems -- Selected Applications -- Part II The Fuzzy Cognitive Network Model: Introduction and Outline -- Existence and Uniqueness of Solutions in FCN -- Adaptive Estimation Algorithms of FCN Parameters -- Framework of Operation and Selected Applications.
520 ## - SUMMARY, ETC.
Summary, etc Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented.  Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model  stems  from fuzzy cognitive maps and uses the notion of "concepts" and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems.  All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: •             contemporary power generation; •             process control; and •             conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control. aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
700 1# - AUTHOR 2
Author 2 Theodoridis, Dimitrios.
700 1# - AUTHOR 2
Author 2 Kottas, Theodore.
700 1# - AUTHOR 2
Author 2 Christodoulou, Manolis A.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-06364-5
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2014.
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-- text
-- txt
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-- computer
-- c
-- rdamedia
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-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Industrial engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Production engineering.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Industrial and Production Engineering.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1430-9491
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-- ZDB-2-ENG

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