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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals

  • Ju H. Park
  • Hao Shen
  • Xiao-Heng Chang
  • Tae H. Lee

Part of the Studies in Systems, Decision and Control book series (SSDC, volume 170)

Table of contents

  1. Front Matter
    Pages i-xxvii
  2. Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee
    Pages 1-18
  3. Control Problems

    1. Front Matter
      Pages 19-19
    2. Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee
      Pages 21-40
    3. Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee
      Pages 41-67
    4. Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee
      Pages 69-84
    5. Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee
      Pages 101-115
  4. Filtering Problems

    1. Front Matter
      Pages 117-117
    2. Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee
      Pages 119-139
    3. Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee
      Pages 173-189
  5. Application Problems

    1. Front Matter
      Pages 191-191
  6. Back Matter
    Pages 225-226

About this book

Introduction

This book introduces the principle theories and applications of control and filtering problems to address emerging hot topics in feedback systems. With the development of IT technology at the core of the 4th industrial revolution, dynamic systems are becoming more sophisticated, networked, and advanced to achieve even better performance. However, this evolutionary advance in dynamic systems also leads to unavoidable constraints. In particular, such elements in control systems involve uncertainties, communication/transmission delays, external noise, sensor faults and failures, data packet dropouts, sampling and quantization errors, and switching phenomena, which have serious effects on the system’s stability and performance. This book discusses how to deal with such constraints to guarantee the system’s design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. It also provides a number of practical examples to show the applicability of the presented methods and techniques.

This book is of interest to graduate students, researchers and professors, as well as R&D engineers involved in control theory and applications looking to analyze dynamical systems with constraints and to synthesize various types of corresponding controllers and filters for optimal performance of feedback systems.

Keywords

Control Filtering Dynamics systems Dynamic networks Synchronization Stability Stabilization Quantization Sampled-data

Authors and affiliations

  • Ju H. Park
    • 1
  • Hao Shen
    • 2
  • Xiao-Heng Chang
    • 3
  • Tae H. Lee
    • 4
  1. 1.Department of Electrical EngineeringYeungnam UniversityKyongsanKorea (Republic of)
  2. 2.School of Electrical and Information EngineeringAnhui University of TechnologyMa’anshanChina
  3. 3.School of Information Science and EngineeringWuhan University of Science and TechnologyWuhanChina
  4. 4.Division of Electronic EngineeringChonbuk National UniversityJeonjuKorea (Republic of)

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-96202-3
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2019
  • Publisher Name Springer, Cham
  • eBook Packages Intelligent Technologies and Robotics
  • Print ISBN 978-3-319-96201-6
  • Online ISBN 978-3-319-96202-3
  • Series Print ISSN 2198-4182
  • Series Online ISSN 2198-4190
  • Buy this book on publisher's site
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