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Intelligent Control

A Stochastic Optimization Based Adaptive Fuzzy Approach

  • Kaushik Das Sharma
  • Amitava Chatterjee
  • Anjan Rakshit

Part of the Cognitive Intelligence and Robotics book series (CIR)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Prologue

    1. Front Matter
      Pages 1-1
    2. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 3-21
    3. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 23-36
    4. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 37-75
  3. Lyapunov Strategy Based Design Methodologies

    1. Front Matter
      Pages 77-77
    2. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 79-100
    3. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 101-156
  4. H∞ Strategy Based Design Methodologies

    1. Front Matter
      Pages 157-157
    2. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 159-174
    3. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 175-206
  5. Applications

    1. Front Matter
      Pages 207-207
    2. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 209-242
    3. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 243-280
    4. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 281-293
  6. Epilogue

    1. Front Matter
      Pages 295-295
    2. Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
      Pages 297-300
  7. Back Matter
    Pages 301-302

About this book

Introduction

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H∞ theory to develop such hybrid control strategies. The goal of developing a series of such hybridization processes is to combine the strengths of both Lyapunov theory/Htheory-based local search methods and stochastic optimization-based global search methods, so as to attain superior control algorithms that can simultaneously achieve desired asymptotic performance and provide improved transient responses. The book also demonstrates how these intelligent adaptive control algorithms can be effectively utilized in real-life applications such as in temperature control for air heater systems with transportation delay, vision-based navigation of mobile robots, intelligent control of robot manipulators etc.

Keywords

Adaptive Control Fuzzy Control Stochastic Optimization Control of Robot Manipulators Vision based Mobile Robot Navigation

Authors and affiliations

  • Kaushik Das Sharma
    • 1
  • Amitava Chatterjee
    • 2
  • Anjan Rakshit
    • 3
  1. 1.Department of Applied PhysicsUniversity of CalcuttaKolkataIndia
  2. 2.Department of Electrical EngineeringJadavpur UniversityKolkataIndia
  3. 3.Department of Electrical EngineeringJadavpur UniversityKolkataIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-13-1298-4
  • Copyright Information Springer Nature Singapore Pte Ltd. 2018
  • Publisher Name Springer, Singapore
  • eBook Packages Computer Science
  • Print ISBN 978-981-13-1297-7
  • Online ISBN 978-981-13-1298-4
  • Series Print ISSN 2520-1956
  • Series Online ISSN 2520-1964
  • Buy this book on publisher's site
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