Optimal Control of Energy Resources for State Estimation Over Wireless Channels

  • Alex S. Leong
  • Daniel E. Quevedo
  • Subhrakanti Dey

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Also part of the SpringerBriefs in Control, Automation and Robotics book sub series (BRIEFSCONTROL)

Table of contents

  1. Front Matter
    Pages i-vii
  2. Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey
    Pages 1-8
  3. Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey
    Pages 9-34
  4. Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey
    Pages 35-64
  5. Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey
    Pages 65-83
  6. Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey
    Pages 85-123
  7. Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey
    Pages 125-125

About this book

Introduction

This brief introduces wireless communications ideas and techniques into the study of networked control systems. It focuses on state estimation problems in which sensor measurements (or related quantities) are transmitted over wireless links to a central observer.

Wireless communications techniques are used for energy resource management in order to improve the performance of the estimator when transmission occurs over packet dropping links, taking energy use into account explicitly in Kalman filtering and control. The brief allows a reduction in the conservatism of control designs by taking advantage of the assumed.

The brief shows how energy-harvesting-based rechargeable batteries or storage devices can offer significant advantages in the deployment of large-scale wireless sensor and actuator networks by avoiding the cost-prohibitive task of battery replacement and allowing self-sustaining sensor to be operation. In contrast with research on energy harvesting largely focused on resource allocation for wireless communication systems design, this brief optimizes estimation objectives such as minimizing the expected estimation error covariance. The resulting power control problems are often stochastic control problems which take into account both system and channel dynamics. The authors show how to pose and solve such design problems using dynamic programming techniques.

Researchers and graduate students studying networked control systems will find this brief a helpful source of new ideas and research approaches.

Keywords

Networked Control Systems Remote Estimation Fading Channels Power Control Energy Harvesting Stochastic Control

Authors and affiliations

  • Alex S. Leong
    • 1
  • Daniel E. Quevedo
    • 2
  • Subhrakanti Dey
    • 3
  1. 1.Faculty of Electrical Engineering and Information Technology (EIM-E)Paderborn UniversityPaderbornGermany
  2. 2.Faculty of Electrical Engineering and Information Technology (EIM-E)Paderborn UniversityPaderbornGermany
  3. 3.Department of Engineering ScienceUppsala UniversityUppsalaSweden

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-65614-4
  • Copyright Information The Author(s) 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-65613-7
  • Online ISBN 978-3-319-65614-4
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • About this book