Intelligent Control (Record no. 57283)

000 -LEADER
fixed length control field 03554nam a22004935i 4500
001 - CONTROL NUMBER
control field 978-3-319-02135-5
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112219.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 131128s2014 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319021355
-- 978-3-319-02135-5
082 04 - CLASSIFICATION NUMBER
Call Number 629.8
100 1# - AUTHOR NAME
Author Siddique, Nazmul.
245 10 - TITLE STATEMENT
Title Intelligent Control
Sub Title A Hybrid Approach Based on Fuzzy Logic, Neural Networks and Genetic Algorithms /
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVII, 282 p. 158 illus., 55 illus. in color.
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Dynamical Systems -- Control Systems -- Mathematics of Fuzzy Control -- Fuzzy Control -- GA-Fuzzy Control -- Neuro-Fuzzy Control -- GA-Neuro-Fuzzy Control -- Stability Analysis -- Epilogue and Future Work.
520 ## - SUMMARY, ETC.
Summary, etc Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined. The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area. Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-02135-5
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2014.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer simulation.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- System theory.
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
-- Systems Theory, Control.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Simulation and Modeling.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1860-949X ;
912 ## -
-- ZDB-2-ENG

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