Since the 1990s, AI-based induction motors have received greater attention and numerous technical papers have been published. At the same time a few good reference books on intelligent control and power electronic drives were published This book aims to explore possible areas of induction motor control that require further investigation and development and focuses on the application of intelligent control principles and algorithms in order to make the controller independent of, or less sensitive to, motor parameter changes. There are twelve chapters, Chapter 1 gives an overview of induction motor drives and reviews previous work in this important technical area. Chapter 2 presents the philosophy of induction motor control. From the classical induction motor model, the differential equations are formulated that fit in a generic control framework. Various control schemes are then discussed, followed by the development of general control algorithms. Modelling and simulation of induction motors is discussed in Chapter 3 with the aid of detailed Matlab/Simulink block diagrams. Chapter 4 is a primer for readers to get started with simulation of various AI techniques. Chapters 3 and 4 together form the basis of the intelligent control schemes discussed in Chapters 5 to 10, which cover, in this order, expert-system-based acceleration control, hybrid fuzzy/PI two-stage control, neural-network-based direct self control, parameter estimation using neural networks, GA-optimized extended Kalman filter for speed estimation, and GA-optimized random PWM generation strategy. Chapter 11 describes the details of the experimental system and presents the experiments and experimental results. Chapter 12 gives some conclusions and explores possible new areas of AI applications to induction motor drives.
