Applied Intelligent Control of Induction Motor Drives (Hardcover)

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

感應電動機是工業中最重要的工作馬力。當它們由固定頻率的電壓源供電時，它們主要用作恆速驅動器。然而，隨著先進的功率電子轉換器和強大的數字信號處理器的出現，高性能、可調速交流電動機驅動器的開發成為可能。

本書旨在探索基於人工智能（AI）技術的感應電動機控制的新領域，以使控制器對參數變化的敏感性降低。選擇的AI技術應用於不同的感應電動機控制策略。本書提供了一個實用的電腦模擬模型，可用於研究各種感應電動機驅動操作。探索的控制策略包括基於專家系統的加速度控制、混合模糊/PI兩級控制、基於神經網絡的直接自控制和基於遺傳算法的擴展卡爾曼濾波器用於轉子速度估計。還有關於基於神經網絡的參數估計、基於遺傳算法的優化隨機PWM策略和實驗研究的章節。本書還提供了一個章節，作為讀者開始進行各種AI技術模擬研究的入門指南。

本書介紹了感應電動機驅動的主要人工智能技術，並使用實用的模擬方法讓感興趣的讀者開始進行驅動器開發。作者是在該領域擁有超過20年經驗的經驗豐富的科學家。本書提供了許多例子和最新的研究結果。書中的模擬程序可從該書的附屬網站下載。

本書對於專攻電動機驅動、電動車輛和電動船推進的研究生和研究工程師非常有價值。智能控制、應用電動運動和能源的研究生，以及工業電子、自動化和電氣運輸的工程師也會發現本書很有幫助。

模擬材料可在www.wiley.com/go/chanmotor上下載。