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Nature-Inspired Computing for Control Systems

  • Book
  • © 2016

Overview

Editors:
  1. Hiram Eredín Ponce Espinosa

    1. Faculty of Engineering, Universidad Panamericana, Mexico City, Mexico

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  • Offers a comprehensive review of nature-inspired methods and applications
  • Describes the advantages of nature-inspired computing in comparison to traditional techniques, with a special emphasis to control engineering applications
  • Reports on cutting-edge research in control systems
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 40)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xii
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  2. The Power of Natural Inspiration in Control Systems

    • Hiram Eredín Ponce Espinosa, José Roberto Ayala-Solares
    Pages 1-10

  4. Control Tuning and Adaptive Control Systems

    1. Front Matter

      Pages 71-71
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    2. Evolutionary Modeling of Industrial Plants and Design of PID Controllers

      • Monica Patrascu, Andreea Ion
      Pages 73-119

    3. Designing Fuzzy Controller for a Class of MIMO Nonlinear Systems Using Hybrid Elite Genetic Algorithm and Tabu Search

      • Nesrine Talbi, Khaled Belarbi
      Pages 121-144

    4. Neural Network Fitting for Input-Output Manifolds in Constrained Linear Systems

      • José M. Araújo, Carlos E. T. Dórea
      Pages 145-167

    5. Adaptive Neuro-Fuzzy Controller of Induction Machine Drive with Nonlinear Friction

      • Abdesselem Boulkroune, Salim Issaouni, Hachemi Chekireb
      Pages 169-192

  5. Robotics Applications

    1. Front Matter

      Pages 193-193
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    2. Fuzzy Logic Sugeno Controller Type-2 For Quadrotors Based on Anfis

      • Pedro Ponce, Arturo Molina, Israel Cayetano, Jose Gallardo, Hugo Salcedo, Jose Rodriguez et al.
      Pages 195-230

    3. Mobile Robot with Movement Detection Controlled by a Real-Time Optical Flow Hermite Transform

      • Ernesto Moya-Albor, Jorge Brieva, Hiram Eredín Ponce Espinosa
      Pages 231-263

    4. Evolutionary Function Approximation for Gait Generation on Legged Robots

      • Oscar A. Silva, Miguel A. Solis
      Pages 265-289
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Keywords

About this book

The book presents recent advances in nature-inspired computing, giving a special emphasis to control systems applications. It reviews different techniques used for simulating physical, chemical, biological or social phenomena at the purpose of designing robust, predictive and adaptive control strategies. The book is a collection of several contributions, covering either more general approaches in control systems, or methodologies for control tuning and adaptive controllers, as well as exciting applications of nature-inspired techniques in robotics. On one side, the book is expected to motivate readers with a background in conventional control systems to try out these powerful techniques inspired by nature. On the other side, the book provides advanced readers with a deeper understanding of the field and a broad spectrum of different methods and techniques. All in all, the book is an outstanding, practice-oriented reference guide to nature-inspired computing addressing graduate students, researchers and practitioners in the field of control engineering.

Editors and Affiliations

  • Faculty of Engineering, Universidad Panamericana, Mexico City, Mexico

    Hiram Eredín Ponce Espinosa

Bibliographic Information

  • Book Title: Nature-Inspired Computing for Control Systems

  • Editors: Hiram Eredín Ponce Espinosa

  • Series Title: Studies in Systems, Decision and Control

  • DOI: https://doi.org/10.1007/978-3-319-26230-7

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing Switzerland 2016

  • Hardcover ISBN: 978-3-319-26228-4Published: 23 December 2015

  • Softcover ISBN: 978-3-319-79910-0Published: 30 March 2019

  • eBook ISBN: 978-3-319-26230-7Published: 16 December 2015

  • Series ISSN: 2198-4182

  • Series E-ISSN: 2198-4190

  • Edition Number: 1

  • Number of Pages: XII, 289

  • Number of Illustrations: 117 b/w illustrations, 62 illustrations in colour

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

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