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Innovations in Intelligent Machines-5

Computational Intelligence in Control Systems Engineering

  • Book
  • © 2014

Overview

Editors:
  1. Valentina Emilia Balas

    1. Department of Automation and Applied Informatics, "Aurel Vlaicu" University of Arad, Arad, Romania

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  2. Petia Koprinkova-Hristova

    1. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

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  3. Lakhmi C. Jain

    1. Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Australia

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  • Presents the emerging computational intelligence paradigms in control systems engineering
  • Including some real world applications
  • Written by leading experts in the field
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 561)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xv
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  2. Decentralized Fuzzy-Neural Identification and I-Term Adaptive Control of Distributed Parameter Bioprocess Plant

    • Ieroham Baruch, Eloy Echeverria Saldierna
    Pages 1-43

  3. Error Tolerant Predictive Control Based on Recurrent Neural Models

    • Petia Georgieva, Sebastião Feyo de Azevedo
    Pages 45-72

  4. Advances in Multiple Models Based Adaptive Switching Control: From Conventional to Intelligent Approaches

    • Nikolaos A. Sofianos, Yiannis S. Boutalis
    Pages 73-108

  5. A Computational Intelligence Approach to Software Component Repository Management

    • D. Vijay Rao, V. V. S. Sarma
    Pages 109-132

  6. A Soft Computing Approach to Model Human Factors in Air Warfare Simulation System

    • D. Vijay Rao, Dana Balas-Timar
    Pages 133-154

  7. Application of Gaussian Processes to the Modelling and Control in Process Engineering

    • Juš Kocijan, Alexandra Grancharova
    Pages 155-190

  8. Computational Intelligence Techniques for Chemical Process Control

    • N. Paraschiv, M. Oprea, M. Cǎrbureanu, M. Olteanu
    Pages 191-226

  9. Application of Swarm Intelligence in Fuzzy Entropy Based Image Segmentation

    • R. Krishna Priya, C. Thangaraj, C. Kesavadas, S. Kannan
    Pages 227-245

  10. Back Matter

    Pages 247-248
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Keywords

About this book

This research monograph presents selected areas of applications in the field of control systems engineering using computational intelligence methodologies. A number of applications and case studies are introduced. These methodologies are increasing used in many applications of our daily lives. Approaches include, fuzzy-neural multi model for decentralized identification, model predictive control based on time dependent recurrent neural network development of cognitive systems, developments in the field of Intelligent Multiple Models based Adaptive Switching Control, designing military training simulators using modelling, simulation, and analysis for operational analyses and training, methods for modelling of systems  based on the application of Gaussian processes, computational intelligence techniques for process control and image segmentation technique based on modified particle swarm optimized-fuzzy entropy.

Editors and Affiliations

  • Department of Automation and Applied Informatics, "Aurel Vlaicu" University of Arad, Arad, Romania

    Valentina Emilia Balas

  • Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Petia Koprinkova-Hristova

  • Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Australia

    Lakhmi C. Jain

Bibliographic Information

  • Book Title: Innovations in Intelligent Machines-5

  • Book Subtitle: Computational Intelligence in Control Systems Engineering

  • Editors: Valentina Emilia Balas, Petia Koprinkova-Hristova, Lakhmi C. Jain

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-662-43370-6

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2014

  • Hardcover ISBN: 978-3-662-43369-0Published: 11 June 2014

  • Softcover ISBN: 978-3-662-52156-4Published: 17 September 2016

  • eBook ISBN: 978-3-662-43370-6Published: 22 May 2014

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XV, 248

  • Number of Illustrations: 129 b/w illustrations

  • Topics: Computational Intelligence, Control and Systems Theory, Artificial Intelligence

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