Modelling and Control of Dynamic Systems Using Gaussian Process Models (Record no. 54054)

000 -LEADER
fixed length control field 03812nam a22005055i 4500
001 - CONTROL NUMBER
control field 978-3-319-21021-6
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421111204.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151121s2016 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319210216
-- 978-3-319-21021-6
082 04 - CLASSIFICATION NUMBER
Call Number 629.8
100 1# - AUTHOR NAME
Author Kocijan, Juš.
245 10 - TITLE STATEMENT
Title Modelling and Control of Dynamic Systems Using Gaussian Process Models
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2016.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVI, 267 p. 117 illus., 17 illus. in color.
490 1# - SERIES STATEMENT
Series statement Advances in Industrial Control,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 System Identification with GP Models -- Incorporation of Prior Knowledge -- Control with GP Models -- Trends, Challenges and Research Opportunities -- Case Studies.
520 ## - SUMMARY, ETC.
Summary, etc This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas-liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB� toolbox, for identification and simulation of dynamic GP models is provided for download. 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.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-21021-6
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2016.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
-- cr
-- rdacarrier
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-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Chemical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Statistics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Industrial Chemistry/Chemical Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1430-9491
912 ## -
-- ZDB-2-ENG

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