Overview
- Explains the basic operation of microbial fuel cells using straightforward language, and can be easily understood by readers with no biology or chemistry background
- Addresses intelligent control-oriented mathematical modeling with uncertain parameters
- Bridges the gap between two groups: (biological and chemical) researchers, and control engineers
- Focuses on the modeling of and control techniques for various microbial fuel cells
- Includes a detailed procedure for creating microbial fuel cells in the laboratory
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 161)
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Table of contents (10 chapters)
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Front Matter
Keywords
About this book
This book addresses a range of solutions and effective control techniques for Microbial Fuel Cells (MFCs), intended as a response to the increased energy consumption and wastewater production stemming from globalization. It describes the fundamentals of MFCs and control-oriented mathematical models, and provides detailed information on uncertain parameters. Various control techniques like robust control with LMI, adaptive backstepping control, and exact linearization control are developed for different mathematical models.
In turn, the book elaborates on the basics of adaptive control, presenting several methods in detail. It also demonstrates how MFCs can be developed at the laboratory level, equipping readers to develop their own MFCs for experimental purposes. In closing, it develops a transfer function model for MFCs by combining a system identification technique and model reference adaptive control techniques. By addressing one of the most promising sources of clean and renewable energy, this book provides a viable solution for meeting the world’s increasing energy demands.
Authors and Affiliations
Bibliographic Information
Book Title: Adaptive and Intelligent Control of Microbial Fuel Cells
Authors: Ravi Patel, Dipankar Deb, Rajeeb Dey, Valentina E. Balas
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-030-18068-3
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-18067-6Published: 03 May 2019
eBook ISBN: 978-3-030-18068-3Published: 16 April 2019
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XIX, 121
Number of Illustrations: 71 illustrations in colour
Topics: Computational Intelligence, Renewable and Green Energy, Electrochemistry, Control and Systems Theory, Artificial Intelligence