Artificial-Intelligence-based Electrical Machines and Drives

Artificial-Intelligence-based Electrical Machines and Drives

Author: Peter Vas

Publisher: Oxford University Press

Published: 1999-01-28

Total Pages: 794

ISBN-13: 9780198593973

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Roughly half of all electricity generated is consumed in motors, and recent efforts to apply artificial intelligence (AI) to improving electric motors are receiving attention worldwide. At present two industrial drives incorporate some form of AI. This book is the first comprehensive discussion of AI applications to electrical machines and drives. It looks at d.c. drives, induction motor drives, synchronous motor drives, switched reluctance motor drives, and sensorless drives. It combines simple explanations of AI-based systems with detailed and unified mathematical and physical treatments, and it includes numerous worked examples, simulations, and experimental results.


Development of Adaptive Speed Observers for Induction Machine System Stabilization

Development of Adaptive Speed Observers for Induction Machine System Stabilization

Author: Ahmed A. Zaki Diab

Publisher: Springer Nature

Published: 2020-01-03

Total Pages: 95

ISBN-13: 9811522987

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This book describes the development of an adaptive state observer using a mathematical model to achieve high performance for sensorless induction motor drives. This involves first deriving an expression for a modified gain rotor flux observer with a parameter adaptive scheme to estimate the motor speed accurately and improve the stability and performance of sensorless vector-controlled induction motor drives. This scheme is then applied to the controls of a photovoltaic-motor water-pumping system, which results in improved dynamic performance under different operating conditions. The book also presents a robust speed controller design for a sensorless vector-controlled induction motor drive system based on H∞ theory, which overcomes the problems of the classical controller.


Sensorless Vector and Direct Torque Control

Sensorless Vector and Direct Torque Control

Author: Peter Vas

Publisher: Oxford, [Eng.] ; New York : Oxford University Press

Published: 1998

Total Pages: 804

ISBN-13:

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This is the first comprehensive book on sensorless high performance a.c. drives. It is essential reading for anyone interestred in acquiring a solid background on sensorless torque-controlled drives. It presents a detailed and unified treatment of sensorless vector-controlled and direct-torque controlled drive systems. It also discusses the applications of artificial intelligence to drives. Where possible, space vector theory is used and emphasis is laid on detailed mathematical and physical analysis. Sensorless drive schemes for different types of permanent magnet synchronous motors, synchronous reluctance motors, and induction motors are also presented. These include more than twenty vector drives e.g. five types of MRAS-based vector drives, and eleven types of direct-torque-controlled (DTC) drives, e.g. the ABB DTC drive. However, torque-controlled switched reluctance motor drives are also discussed due to their emerging importance. The book also covers various drive applications using artificial intelligence (fuzzy logic, neural networks, fuzzy-neural networks) and AI-based modelling of electrical machines. Finally, self-commissioning techniques are also discussed. This is a comprehensive thoroughly up-to-date, and self-contained book suitable for students at various levels, teachers, and industrial readership. Peter Vas is a Professor at the Department of Engineering at the University of Aberdeen, UK, where he is also the Head of the Intelligent Motion Control Group. His previous books published by Oxford University Press are extensively used worldwide.


Advanced and Intelligent Control in Power Electronics and Drives

Advanced and Intelligent Control in Power Electronics and Drives

Author: Teresa Orłowska-Kowalska

Publisher: Springer

Published: 2014-01-08

Total Pages: 422

ISBN-13: 3319034014

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Power electronics and variable frequency drives are continuously developing multidisciplinary fields in electrical engineering and it is practically not possible to write a book covering the entire area by one individual specialist. Especially by taking account the recent fast development in the neighboring fields like control theory, computational intelligence and signal processing, which all strongly influence new solutions in control of power electronics and drives. Therefore, this book is written by individual key specialist working on the area of modern advanced control methods which penetrates current implementation of power converters and drives. Although some of the presented methods are still not adopted by industry, they create new solutions with high further research and application potential. The material of the book is presented in the following three parts: Part I: Advanced Power Electronic Control in Renewable Energy Sources (Chapters 1-4), Part II: Predictive Control of Power Converters and Drives (5-7), Part III: Neurocontrol and Nonlinear Control of Power Converters and Drives (8-11). The book is intended for engineers, researchers and students in the field of power electronics and drives who are interested in the use of advanced control methods and also for specialists from the control theory area who like to explore new area of applications.


Advances in Electrical Engineering and Computational Science

Advances in Electrical Engineering and Computational Science

Author: Len Gelman

Publisher: Springer Science & Business Media

Published: 2009-04-21

Total Pages: 728

ISBN-13: 9048123119

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Advances in Electrical Engineering and Computational Science contains sixty-one revised and extended research articles written by prominent researchers participating in the conference. Topics covered include Control Engineering, Network Management, Wireless Networks, Biotechnology, Signal Processing, Computational Intelligence, Computational Statistics, Internet Computing, High Performance Computing, and industrial applications. Advances in Electrical Engineering and Computational Science will offer the state of art of tremendous advances in electrical engineering and computational science and also serve as an excellent reference work for researchers and graduate students working with/on electrical engineering and computational science.


Condition Monitoring of Machinery in Non-Stationary Operations

Condition Monitoring of Machinery in Non-Stationary Operations

Author: Tahar Fakhfakh

Publisher: Springer Science & Business Media

Published: 2012-03-19

Total Pages: 621

ISBN-13: 3642287689

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Condition monitoring of machines in non-stationary operations (CMMNO) can be seen as the major challenge for research in the field of machinery diagnostics. Condition monitoring of machines in non-stationary operations is the title of the presented book and the title of the Conference held in Hammamet - Tunisia March 26 – 28, 2012. It is the second conference under this title, first took place in Wroclaw - Poland , March 2011. The subject CMMNO comes directly from industry needs and observation of real objects. Most monitored and diagnosed objects used in industry works in non-stationary operations condition. The non-stationary operations come from fulfillment of machinery tasks, for which they are designed for. All machinery used in different kind of mines, transport systems, vehicles like: cars, buses etc, helicopters, ships and battleships and so on work in non-stationary operations. The papers included in the book are shaped by the organizing board of the conference and authors of the papers. The papers are divided into five sections, namely: Condition monitoring of machines in non-stationary operations Modeling of dynamics and fault in systems Signal processing and Pattern recognition Monitoring and diagnostic systems Noise and vibration of machines The presented book gives the back ground to the main objective of the CMMNO 2012 conference that is to bring together scientific community to discuss the major advances in the field of machinery condition monitoring in non-stationary conditions.


Artificial Intelligent Techniques for Electric and Hybrid Electric Vehicles

Artificial Intelligent Techniques for Electric and Hybrid Electric Vehicles

Author: Chitra A.

Publisher: John Wiley & Sons

Published: 2020-07-10

Total Pages: 278

ISBN-13: 1119682010

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Electric vehicles are changing transportation dramatically and this unique book merges the many disciplines that contribute research to make EV possible, so the reader is informed about all the underlying science and technologies driving the change. An emission-free mobility system is the only way to save the world from the greenhouse effect and other ecological issues. This belief has led to a tremendous growth in the demand for electric vehicles (EV) and hybrid electric vehicles (HEV), which are predicted to have a promising future based on the goals fixed by the European Commission's Horizon 2020 program. This book brings together the research that has been carried out in the EV/HEV sector and the leading role of advanced optimization techniques with artificial intelligence (AI). This is achieved by compiling the findings of various studies in the electrical, electronics, computer, and mechanical domains for the EV/HEV system. In addition to acting as a hub for information on these research findings, the book also addresses the challenges in the EV/HEV sector and provides proven solutions that involve the most promising AI techniques. Since the commercialization of EVs/HEVs still remains a challenge in industries in terms of performance and cost, these are the two tradeoffs which need to be researched in order to arrive at an optimal solution. Therefore, this book focuses on the convergence of various technologies involved in EVs/HEVs. Since all countries will gradually shift from conventional internal combustion (IC) engine-based vehicles to EVs/HEVs in the near future, it also serves as a useful reliable resource for multidisciplinary researchers and industry teams.


Advances in Control Technologies for Brushless Doubly-fed Induction Generators

Advances in Control Technologies for Brushless Doubly-fed Induction Generators

Author: Yi Liu

Publisher: Springer Nature

Published: 2022-03-06

Total Pages: 418

ISBN-13: 9811904243

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This book presents advances in control technologies for efficient operation of the brushless doubly-fed induction generator (BDFIG). For robust and low-cost operation of BDFIGs, it is required to keep high-quality output voltage and eliminate the speed/position encoder under different loads and operation conditions. Some advanced control technologies, from the authors’ latest work on these topics, are presented to achieve this goal with simple and accurate texts, illustrations, and tables. The qualified outcomes obtained from this book assure the high-performance operation of BDFIGs and also give the readers a straight insight toward challenges in this research area in the future.


Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

Author: Vinit Kumar Gunjan

Publisher: Springer Nature

Published: 2021-04-26

Total Pages: 515

ISBN-13: 3030682919

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This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems – theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.