Book description
Induction motors are the most important workhorses in industry. They
are mostly used as constant-speed drives when fed from a voltage source
of fixed frequency. Advent of advanced power electronic converters and
powerful digital signal processors, however, has made possible the
development of high performance, adjustable speed AC motor drives.
This book aims to explore new areas of induction motor control based
on artificial intelligence (AI) techniques in order to make the
controller less sensitive to parameter changes. Selected AI techniques
are applied for different induction motor control strategies. The book
presents a practical computer simulation model of the induction motor
that could be used for studying various induction motor drive
operations. The control strategies explored include
expert-system-based acceleration control, hybrid-fuzzy/PI two-stage
control, neural-network-based direct self control, and genetic
algorithm based extended Kalman filter for rotor speed estimation.
There are also chapters on neural-network-based parameter estimation,
genetic-algorithm-based optimized random PWM strategy, and
experimental investigations. A chapter is provided as a primer for
readers to get started with simulation studies on various AI techniques.
- Presents major artificial intelligence techniques to induction
motor drives
- Uses a practical simulation approach to get interested readers
started on drive development
- Authored by experienced scientists with over 20 years of
experience in the field
- Provides numerous examples and the latest research results
- Simulation programs available from the book's Companion Website
This book will be invaluable to graduate students and research
engineers who specialize in electric motor drives, electric vehicles,
and electric ship propulsion. Graduate students in intelligent
control, applied electric motion, and energy, as well as engineers in
industrial electronics, automation, and electrical transportation,
will also find this book helpful.
Simulation materials available for download at www. wiley.
com/go/chanmotor
Tze-Fun Chan is an associate professor of
electrical engineering at the Hong Kong Polytechnic University, where
he has been working for over 30 years since 1978. Chan's research
interests are self-excited induction generators, brushless AC
generators, permanent-magnet machines, finite element analysis of
electric machines, and electric motor drives control. In June 2006,
Chan was awarded a Prize Paper by IEEE Power Engineering Society Power
Generation and Energy Development Committee. In 2007, Chan co-authored
a book published by Wiley. He received the B. Sc. and M. Phil degrees
in electrical engineering from the University of Hong Kong in 1974 and
1980 respectively. He received his PhD degree in electrical
engineering from City University London in 2005.
Keli Shi is a Research Engineer of Netpower Technologies Inc..
His research interests are DSP applications and intelligent control of
induction and permanent magnet machines. He received his BS degree in
electronics and electrical engineering from Chengdu University of
Science and Technology and MS degree in electrical engineering from
Harbin Institute of Technology in 1983 and 1989 respectively. He
received his PhD in electrical engineering from The Hong Kong
Polytechnic University in 2001.
