Artificial Intelligence for Power Electronics
Author:Ahteshamul Haque (Editor), Ahteshamul Haque, Saad Mekhilef (Editor), Saad Mekhilef, Azra Malik (Editor), Azra Malik
Publisher finelybook 出版社: Wiley-IEEE Press
Publication Date 出版日期: 2025-07-29
Edition 版本: 1st
Language 语言: English
Print Length 页数: 400 pages
ISBN-10: 1394270771
ISBN-13: 9781394270774
Book Description
Thorough review of how artificial intelligence can enhance the design, control, and optimization of power electronics systems
Artificial Intelligence for Power Electronics provides a comprehensive overview of the intersection between artificial intelligence (AI) and the field of power electronics, exploring how AI can revolutionize and enhance the design, control, and optimization of power electronics systems. The book covers the fundamentals of AI and power electronics, and the challenges the field faces in design to production, with the solutions of these challenges through AI methods. Example solutions, along with Q&A review sections, are included throughout the text, with coverage of both Python and MATLAB.
Some of the topics discussed in this book include:
- Supervised, unsupervised, and reinforcement machine learning and the role of data in training machine learning models
- Techniques for AI data collection in power electronics and how to clean, normalize, and handle missing values of data
- Optimization techniques such as Particle Swarm Optimization and Ant Colony Optimization
- Detection techniques for identifying faults and anomalies and clustering algorithms to group similar operational behavior
- Essential Python libraries for machine learning and how to perform machine learning on a Raspberry Pi
Delivering an industry-specific approach to AI applications, Artificial Intelligence for Power Electronics is a helpful reference for undergraduate, postgraduate, and PhD students in electrical, electronic, and computer engineering. Mechanical engineers and other industry professionals may also find it valuable.
Editorial Reviews
From the Back Cover
Thorough review of how artificial intelligence can enhance the design, control, and optimization of power electronics systems
Artificial Intelligence for Power Electronics provides a comprehensive overview of the intersection between artificial intelligence (AI) and the field of power electronics, exploring how AI can revolutionize and enhance the design, control, and optimization of power electronics systems. The book covers the fundamentals of AI, the fundamentals of power electronics and the challenges the field faces in design to production, and the solutions of these challenges through AI methods. Example solutions, along with Q&A review sections, are included throughout the text, with coverage of both Python and MATLAB.
Topics discussed in Artificial Intelligence for Power Electronics include:
- Supervised, unsupervised, and reinforcement machine learning and the role of data in training machine learning models
- Techniques for AI data collection in power electronics and how to clean, normalize, and handle missing values of data
- Optimization techniques such as Particle Swarm Optimization and Ant Colony Optimization
- Detection techniques for identifying faults and anomalies and clustering algorithms to group similar operational behavior
- Essential Python libraries for machine learning and how to perform machine learning on a Raspberry Pi
Delivering an industry-specific approach to AI applications, Artificial Intelligence for Power Electronics is a helpful reference for undergraduate, postgraduate, and PhD students in electrical, electronic, and computer engineering. Mechanical engineers and other industry professionals may also find it valuable.
About the Author
Dr. Ahteshamul Haque is Professor with the Department of Electrical Engineering, Jamia Millia Islamia, New Delhi, India.
Dr. Saad Mekhilef is an IEEE Fellow and a Distinguished Professor at the School of Engineering, Swinburne University of Technology, Melbourne, Australia.
Dr. Azra Malik is a Post Doctoral Fellow with the Department of Electrical Engineering, IIT Roorkee, Uttarakhand, India.
