Details
Adaptive and Intelligent Control of Microbial Fuel Cells
Intelligent Systems Reference Library, Band 161
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96,29 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 16.04.2019 |
| ISBN/EAN: | 9783030180683 |
| Sprache: | englisch |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<p>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. </p>
<p>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. </p><br>
<p>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. </p><br>
Introduction.- Mathematical Modelling.- Model Analysis of Single Population Single Chamber MFC.- Robust Control design of SPSC Microbial Fuel Cell with norm bounded uncertainty.- Introduction to Adaptive Control.
<p></p><p>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. </p>
<p>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. </p><br><p></p>
<p>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. </p><br><p></p>
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
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