[Studies in Fuzziness and Soft Computing] Complex System Modelling and Control Through Intelligent Soft Computations Volume 319 ||

Download [Studies in Fuzziness and Soft Computing] Complex System Modelling and Control Through Intelligent Soft Computations Volume 319 ||

Post on 03-Apr-2017

229 views

Category:

Documents

12 download

Embed Size (px)

TRANSCRIPT

<ul><li><p>Studies in Fuzziness and Soft Computing</p><p>QuanminZhuAhmadTaherAzar Editors </p><p>Complex System Modelling and Control Through Intelligent Soft Computations</p></li><li><p>Studies in Fuzziness and Soft Computing</p><p>Volume 319</p><p>Series editor</p><p>Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Polande-mail: kacprzyk@ibspan.waw.pl</p></li><li><p>About this Series</p><p>The series Studies in Fuzziness and Soft Computing contains publications onvarious topics in the area of soft computing, which include fuzzy sets, rough sets,neural networks, evolutionary computation, probabilistic and evidential reasoning,multi-valued logic, and related fields. The publications within Studies in Fuzzinessand Soft Computing are primarily monographs and edited volumes. They coversignificant recent developments in the field, both of a foundational and applicablecharacter. An important feature of the series is its short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results.</p><p>More information about this series at http://www.springer.com/series/2941</p><p>http://www.springer.com/series/2941</p></li><li><p>Quanmin Zhu Ahmad Taher AzarEditors</p><p>Complex System Modellingand Control ThroughIntelligent SoftComputations</p><p>123</p></li><li><p>EditorsQuanmin ZhuDepartment of Engineering Designand Mathematics</p><p>University of the West of EnglandBristolUK</p><p>Ahmad Taher AzarFaculty of Computers and InformationBenha UniversityBenhaEgypt</p><p>ISSN 1434-9922 ISSN 1860-0808 (electronic)Studies in Fuzziness and Soft ComputingISBN 978-3-319-12882-5 ISBN 978-3-319-12883-2 (eBook)DOI 10.1007/978-3-319-12883-2</p><p>Library of Congress Control Number: 2014957496</p><p>Springer Cham Heidelberg New York Dordrecht London Springer International Publishing Switzerland 2015This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or partof the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmissionor information storage and retrieval, electronic adaptation, computer software, or by similar ordissimilar methodology now known or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in thispublication does not imply, even in the absence of a specific statement, that such names are exemptfrom the relevant protective laws and regulations and therefore free for general use.The publisher, the authors and the editors are safe to assume that the advice and information in thisbook are believed to be true and accurate at the date of publication. Neither the publisher nor theauthors or the editors give a warranty, express or implied, with respect to the material containedherein or for any errors or omissions that may have been made.</p><p>Printed on acid-free paper</p><p>Springer International Publishing AG Switzerland is part of Springer Science+Business Media(www.springer.com)</p></li><li><p>Preface</p><p>Soft computing-based inductive approaches are concerned with the use of theoriesof fuzzy logic, neural networks and evolutionary computing to solve real-worldproblems that cannot be satisfactorily solved using conventional crisp computingtechniques. Representation and processing of human knowledge, qualitative andapproximate reasoning, computational intelligence, computing with words, andbiological models of problem solving and optimization form key characteristics ofsoft computing, and are directly related to intelligent systems and applications. Inrecent years there has been rapid growth in the development and implementation ofsoft computing techniques in a wide range of applications, particularly those relatedto natural and man-made science and engineering systems.</p><p>This book is intended to present important applications of soft computing asreported from both analytical and practical points of view. The material is organizedinto 29 chapters. In its chapters, the book gives a prime introduction to soft computingwith its principal components of fuzzy logic, neural networks, genetic algorithms andgenetic programming with a self-contained, simple, readable approach. The bookalso includes a few of representative papers to cover industrial and development effortin the applications of intelligent systems through soft computing, which is given toguide the interested readers on their ad hoc applications. Advanced topics and futurechallenges are addressed as well, with the researchers in the field in mind. Theintroductory material, application-oriented techniques, and case studies should beparticularly useful to practicing professionals. In brief summary, this book provides ageneral foundation for soft computing-based inductive methodologies/algorithms aswell as their applications, in terms of providing multidisciplinary solutions in com-plex system modelling and control.</p><p>As the editors, we hope that the chapters in this book will stimulate furtherresearch in Complex system modelling and utilize them in real-world applications.We hope that this book, covering so many different aspects, will be of value to allreaders.</p><p>The editors would like to take this opportunity to thank all the authors for theircontributions to this textbook. Without the hard work of our contributors, this bookwould not have been possible. The encouragement and patience of Series Editor,</p><p>v</p></li><li><p>Prof. Janusz Kacprzyk and Dr. Leontina Di Cecco is very much appreciated.Without their continuous help and assistance during the entire course of this project,the production of the book would have taken a great deal longer. Special thanks toHolger Schaepe for her great effort during the publication process.</p><p>Bristol, UK Quanmin ZhuBenha, Egypt Ahmad Taher Azar</p><p>vi Preface</p></li><li><p>Contents</p><p>Design and Modeling of Anti Wind Up PID Controllers . . . . . . . . . . . 1Ahmad Taher Azar and Fernando E. Serrano</p><p>A Hybrid Global Optimization Algorithm: Particle SwarmOptimization in Association with a Genetic Algorithm. . . . . . . . . . . . . 45M. Andalib Sahnehsaraei, M.J. Mahmoodabadi, M. Taherkhorsandi,K.K. Castillo-Villar and S.M. Mortazavi Yazdi</p><p>Fuzzy Adaptive Controller for a DFI-Motor . . . . . . . . . . . . . . . . . . . . 87Namane Bounar, Abdesselem Boulkroune and Fares Boudjema</p><p>Expert-Based Method of Integrated Waste Management Systemsfor Developing Fuzzy Cognitive Map . . . . . . . . . . . . . . . . . . . . . . . . . 111Adrienn Buruzs, Mikls F. Hatwgner and Lszl T. Kczy</p><p>Leukocyte Detection Through an Evolutionary Method . . . . . . . . . . . . 139Erik Cuevas, Margarita Daz and Ral Rojas</p><p>PWARX Model Identification Based on Clustering Approach . . . . . . . 165Zeineb Lassoued and Kamel Abderrahim</p><p>Supplier Quality Evaluation Using a Fuzzy Multi CriteriaDecision Making Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195Anjali Awasthi</p><p>Concept Trees: Building Dynamic Concepts from Semi-structuredData Using Nature-Inspired Methods . . . . . . . . . . . . . . . . . . . . . . . . . 221Kieran Greer</p><p>vii</p><p>http://dx.doi.org/10.1007/978-3-319-12883-2_1http://dx.doi.org/10.1007/978-3-319-12883-2_2http://dx.doi.org/10.1007/978-3-319-12883-2_2http://dx.doi.org/10.1007/978-3-319-12883-2_3http://dx.doi.org/10.1007/978-3-319-12883-2_4http://dx.doi.org/10.1007/978-3-319-12883-2_4http://dx.doi.org/10.1007/978-3-319-12883-2_5http://dx.doi.org/10.1007/978-3-319-12883-2_6http://dx.doi.org/10.1007/978-3-319-12883-2_7http://dx.doi.org/10.1007/978-3-319-12883-2_7http://dx.doi.org/10.1007/978-3-319-12883-2_8http://dx.doi.org/10.1007/978-3-319-12883-2_8</p></li><li><p>Swarm Intelligence Techniques and Their Adaptive Naturewith Applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253Anupam Biswas and Bhaskar Biswas</p><p>Signal Based Fault Detection and Diagnosis for RotatingElectrical Machines: Issues and Solutions . . . . . . . . . . . . . . . . . . . . . . 275Andrea Giantomassi, Francesco Ferracuti, Sabrina Iarlori,Gianluca Ippoliti and Sauro Longhi</p><p>Modelling of Intrusion Detection System Using ArtificialIntelligenceEvaluation of Performance Measures . . . . . . . . . . . . . . . 311Manojit Chattopadhyay</p><p>Enhanced Power System Security Assessment ThroughIntelligent Decision Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337Venkat Krishnan</p><p>Classification of Normal and Epileptic Seizure EEG SignalsBased on Empirical Mode Decomposition . . . . . . . . . . . . . . . . . . . . . . 367Ram Bilas Pachori, Rajeev Sharma and Shivnarayan Patidar</p><p>A Rough Set Based Total Quality Management Approachin Higher Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389Ahmad Taher Azar, Renu Vashist and Ashutosh Vashishtha</p><p>Iterative Dual Rational Krylov and Iterative SVD-Dual RationalKrylov Model Reduction for Switched Linear Systems . . . . . . . . . . . . 407Kouki Mohamed, Abbes Mehdi and Abdelkader Mami</p><p>Household Electrical Consumptions Modeling and ManagementThrough Neural Networks and Fuzzy Logic Approaches . . . . . . . . . . . 437Lucio Ciabattoni, Massimo Grisostomi, Gianluca Ippolitiand Sauro Longhi</p><p>Modeling, Identification and Control of Irrigation Stationwith Sprinkling: Takagi-Sugeno Approach . . . . . . . . . . . . . . . . . . . . . 469Wael Chakchouk, Abderrahmen Zaafouri and Anis Sallami</p><p>Review and Improvement of Several Optimal IntelligentPitch Controllers and Estimator of WECS via ArtificialIntelligent Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501Hadi Kasiri, Hamid Reza Momeni and Mohammad Saniee Abadeh</p><p>viii Contents</p><p>http://dx.doi.org/10.1007/978-3-319-12883-2_9http://dx.doi.org/10.1007/978-3-319-12883-2_9http://dx.doi.org/10.1007/978-3-319-12883-2_10http://dx.doi.org/10.1007/978-3-319-12883-2_10http://dx.doi.org/10.1007/978-3-319-12883-2_11http://dx.doi.org/10.1007/978-3-319-12883-2_11http://dx.doi.org/10.1007/978-3-319-12883-2_12http://dx.doi.org/10.1007/978-3-319-12883-2_12http://dx.doi.org/10.1007/978-3-319-12883-2_13http://dx.doi.org/10.1007/978-3-319-12883-2_13http://dx.doi.org/10.1007/978-3-319-12883-2_14http://dx.doi.org/10.1007/978-3-319-12883-2_14http://dx.doi.org/10.1007/978-3-319-12883-2_15http://dx.doi.org/10.1007/978-3-319-12883-2_15http://dx.doi.org/10.1007/978-3-319-12883-2_16http://dx.doi.org/10.1007/978-3-319-12883-2_16http://dx.doi.org/10.1007/978-3-319-12883-2_17http://dx.doi.org/10.1007/978-3-319-12883-2_17http://dx.doi.org/10.1007/978-3-319-12883-2_18http://dx.doi.org/10.1007/978-3-319-12883-2_18http://dx.doi.org/10.1007/978-3-319-12883-2_18</p></li><li><p>Secondary and Tertiary Structure Prediction of Proteins:A Bioinformatic Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541Minu Kesheri, Swarna Kanchan, Shibasish Chowdhuryand Rajeshwar Prasad Sinha</p><p>Approximation of Optimized Fuzzy Logic Controllerfor Shunt Active Power Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 571Asheesh K. Singh, Rambir Singh and Rakesh K. Arya</p><p>Soft Computing Techniques for Optimal Capacitor Placement . . . . . . . 597Pradeep Kumar and Asheesh K. Singh</p><p>Advanced Metaheuristics-Based Approach for Fuzzy ControlSystems Tuning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 627Soufiene Bouallgue, Fatma Toumi, Joseph Haggge and Patrick Siarry</p><p>Robust Estimation Design for Unknown Inputs Fuzzy BilinearModels: Application to Faults Diagnosis . . . . . . . . . . . . . . . . . . . . . . . 655Dhikra Saoudi, Mohammed Chadli and Naceur Benhadj Braeik</p><p>Unit Commitment Optimization Using Gradient-Genetic Algorithmand Fuzzy Logic Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 687Sahbi Marrouchi and Souad Chebbi</p><p>Impact of Hardware/Software Partitioning and MicroBlazeFPGA Configurations on the Embedded Systems Performances . . . . . . 711Imne Mhadhbi, Nabil Litayem, Slim Ben Othman and Slim Ben Saoud</p><p>A Neural Approach to Cursive Handwritten CharacterRecognition Using Features Extracted from BinarizationTechnique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 745Amit Choudhary, Savita Ahlawat and Rahul Rishi</p><p>System Identification Technique and Neural Networksfor Material Lifetime Assessment Application . . . . . . . . . . . . . . . . . . . 773Mas Irfan P. Hidayat</p><p>Measuring Software Reliability: A Trend Using MachineLearning Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 807Nishikant Kumar and Soumya Banerjee</p><p>Hybrid Metaheuristic Approach for Schedulingof Aperiodic OS Tasks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 831Hamza Gharsellaoui and Samir Ben Ahmed</p><p>Contents ix</p><p>http://dx.doi.org/10.1007/978-3-319-12883-2_19http://dx.doi.org/10.1007/978-3-319-12883-2_19http://dx.doi.org/10.1007/978-3-319-12883-2_20http://dx.doi.org/10.1007/978-3-319-12883-2_20http://dx.doi.org/10.1007/978-3-319-12883-2_21http://dx.doi.org/10.1007/978-3-319-12883-2_22http://dx.doi.org/10.1007/978-3-319-12883-2_22http://dx.doi.org/10.1007/978-3-319-12883-2_23http://dx.doi.org/10.1007/978-3-319-12883-2_23http://dx.doi.org/10.1007/978-3-319-12883-2_24http://dx.doi.org/10.1007/978-3-319-12883-2_24http://dx.doi.org/10.1007/978-3-319-12883-2_25http://dx.doi.org/10.1007/978-3-319-12883-2_25http://dx.doi.org/10.1007/978-3-319-12883-2_26http://dx.doi.org/10.1007/978-3-319-12883-2_26http://dx.doi.org/10.1007/978-3-319-12883-2_26http://dx.doi.org/10.1007/978-3-319-12883-2_27http://dx.doi.org/10.1007/978-3-319-12883-2_27http://dx.doi.org/10.1007/978-3-319-12883-2_28http://dx.doi.org/10.1007/978-3-319-12883-2_28http://dx.doi.org/10.1007/978-3-319-12883-2_29http://dx.doi.org/10.1007/978-3-319-12883-2_29</p></li><li><p>Design and Modeling of Anti Wind UpPID Controllers</p><p>Ahmad Taher Azar and Fernando E. Serrano</p><p>Abstract In this chapter several anti windup control strategies for SISO andMIMO systems are proposed to diminish or eliminate the unwanted effects pro-duced by this phenomena, when it occurs in PI or PID controllers. Windup is aphenomena found in PI and PID controllers due to the increase in the integral actionwhen the input of the system is saturated according to the actuator limits. As it isknown, the actuators have physical limits, for this reason, the input of the controllermust be saturated in order to avoid damages. When a PI or PID controller saturates,the integral part of the controller increases its magnitude producing performancedeterioration or even instability. In this chapter several anti windup controllers areproposed to eliminate the effects yielded by this phenomena. The first part of thechapter is devoted to explain classical anti windup architectures implemented inSISO and MIMO systems. Then in the second part of the chapter, the developmentof an anti windup controller for SISO systems is shown based on the approximationof the saturation model. The derivation of PID SISO (single input single output)anti windup controllers for continuous and discrete time systems is implementedadding an anti windup compensator in the feedback loop, so the unwan...</p></li></ul>

Recommended

View more >