Applied Intelligent Control of Induction Motor Drives

The prelims comprise:
Half-Title Page
Title Page
Copyright Page
Table of Contents
Preface
Acknowledgments
About the Authors
List of Symbols View full abstract»

A historical account of induction motor control is given, including scalar control, vector control, speed sensorless control and intelligent control. The contents of the book are briefly reviewed. View full abstract»

Induction motor control is explained from the perspectives of motor theory and control algorithms. The hardware requirements of a modern induction motor drive are briefly mentioned. A taxonomy of induction motor control is given. View full abstract»

Transient models of a three-phase induction motor are established. Functional blocks of the entire inverter-fed induction motor drive system are developed systematically. Programming examples are given to familiarize readers with MATLAB®/Simulink programming environment. View full abstract»

This chapter presents the fundamentals of intelligent control simulation using MATLAB®/Simulink. Modeling and simulation of a fuzzy logic based PI controller, neural network based Park's transformation, signal measurement using Kalman filter, and a genetic algorithm optimized PID controller are discussed. View full abstract»

An acceleration control scheme for an induction motor drive is developed using an expert system approach. The acceleration increments produced by two different voltage vectors are compared to give an optimum stator voltage vector which is selected and retained. The on-line inference control is built using an expert system with heuristic knowledge about the relationship between the motor voltage and acceleration. The feasibility of the proposed system is validated by simulation studies. View full abstract»

Based on the two-stage strategy and the heuristics deduced from the field-oriented principle, a hybrid fuzzy/PI controller is proposed in this chapter. A fuzzy logic controller provides frequency control during the acceleration/deceleration stage, giving a large torque. A PI controller provides speed control by regulating the current magnitude during the steady-state stage. The performance of the two-stage controller approximates that of a field-oriented controller. Besides, the new controller has the advantages of simplicity and insensitivity to motor parameter changes. View full abstract»

In this chapter, implementation of direct self control for an induction motor drive using artificial neural network (ANN) is discussed. The computationally intensive direct self control is implemented using ANNs. Fixed weight and supervised networks with individual training strategy are employed for the ANN controller design. Neural-network based DSC is fast, giving very small steady-state control error. View full abstract»

This chapter describes an integral model for an induction motor which can be implemented conveniently using artificial neural networks. The coefficients of the integral equations are obtained by proper training of the neural networks using actual motor test data and a realistic simulation model of the induction motor can be constructed. View full abstract»

In this chapter, a speed-sensorless controller using an extended Kalman filter (EKF) is investigated. To improve the performance of the speed-sensorless controller, noise covariance and weight matrices of the EKF are optimized by using a real-coded genetic algorithm (GA). MATLAB®/Simulink based simulation results are presented to confirm the efficacy of the GA-optimized EKF for speed estimation in an induction motor drive. View full abstract»

In this chapter, real-coded genetic algorithm is employed to optimize a single-phase inverter controlled by random PWM methods. The simulation studies show that the GA-optimized random PWM is superior to conventional PWM techniques when harmonic energy spread and THD are considered. DSP-based inverter experiments confirm the feasibility of implementation of GA-optimized random-carrier-frequency PWM. View full abstract»

This chapter discusses how a low-cost functional experimental drive system with data acquisition capability is implemented using ADMC331 DSP. The system enables experimental studies on motor run up, fuzzy/PI control, and GA-EKF speed estimation to be performed. Modern DSP programming techniques for induction motor control are presented with reference to the TMS320F28335 processor. These techniques enable the necessary signals to be acquired and transferred to the host PC in real-time for use by a complex control algorithm. View full abstract»

This chapter summarizes the contributions of the book on intelligent control of induction motor drives. Potential industrial applications of these intelligent induction motor drives are discussed. A few new research topics on intelligent induction motor control are reviewed. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»

No abstract. View full abstract»