eBook - Applied Intelligent Control of Induction Motor Drives
Available Exclusively as an eBook | Part of the AI eBook Collection | Only for Institutional Purchase | Publication Year: 2011
Description
This book explores advanced artificial intelligence techniques for controlling induction motor drives, including expert systems, fuzzy logic, neural networks, and genetic algorithms. It emphasizes practical simulation models and control strategies for high-performance, adjustable-speed AC motor drives, targeting graduate students and engineers in electric motor drives and intelligent control applications.
Table of Contents
1 Introduction
2 Philosophy of Induction Motor Control
3 Modeling and Simulation of Induction Motor
4 Fundamentals of Intelligent Control Simulation
5 Expert-System-based Acceleration Control
6 Hybrid Fuzzy/PI Two-Stage Control
7 Neural-Network-based Direct Self Control
8 Parameter Estimation Using Neural Networks
9 GA-Optimized Extended Kalman Filter for Speed Estimation
10 Optimized Random PWM Strategies Based On Genetic Algorithms
11 Experimental Investigations
12 Conclusions and Future Developments
Appendix A Equivalent Circuits of an Induction Motor
Appendix B Parameters of Induction Motors
Appendix C M-File of Discrete-State Induction Motor Model
Appendix D Expert-System Acceleration Control Algorithm
Appendix E Activation Functions of Neural Network
Appendix F M-File of Extended Kalman Filter
Appendix G ADMC331-based Experimental System
Appendix H Experiment 1: Measuring the Electrical Parameters of Motor 3
Appendix I DSP Source Code for the Main Program of Experiment 2
Appendix J DSP Source Code for the Main Program of Experiment 3
Index