
Intelligent Control Systems Using Soft Computing Methodologies
- 504 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Intelligent Control Systems Using Soft Computing Methodologies
About this book
In recent years, intelligent control has emerged as one of the most active and fruitful areas of research and development. Until now, however, there has been no comprehensive text that explores the subject with focus on the design and analysis of biological and industrial applications. Intelligent Control Systems Using Soft Computing Methodologies does all that and more.
Beginning with an overview of intelligent control methodologies, the contributors present the fundamentals of neural networks, supervised and unsupervised learning, and recurrent networks. They address various implementation issues, then explore design and verification of neural networks for a variety of applications, including medicine, biology, digital signal processing, object recognition, computer networking, desalination technology, and oil refinery and chemical processes.
The focus then shifts to fuzzy logic, with a review of the fundamental and theoretical aspects, discussion of implementation issues, and examples of applications, including control of autonomous underwater vehicles, navigation of space vehicles, image processing, robotics, and energy management systems. The book concludes with the integration of genetic algorithms into the paradigm of soft computing methodologies, including several more industrial examples, implementation issues, and open problems and open problems related to intelligent control technology.
Suitable as a textbook or a reference, Intelligent Control Systems explores recent advances in the field from both the theoretical and the practical viewpoints. It also integrates intelligent control design methodologies to give designers a set of flexible, robust controllers and provide students with a tool for solving the examples and exercises within the book.
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Table of contents
- Cover Page
- Halftitle Page
- Halftitle Page
- Copyright Page
- Dedication Page
- PREFACE
- ABOUT THE EDITORS
- CONTRIBUTORS
- ABBREVIATIONS
- Table of Contents
- 1 INTRODUCTION
- 2 FUNDAMENTALS OF NEURAL NETWORKS
- 3 NEURAL NETWORK ARCHITECTURES
- 4 APPLICATIONS OF NEURAL NETWORKS IN MEDICINE AND BIOLOGICAL SCIENCES
- 5 APPLICATION OF NEURAL NETWORK IN DESIGN OF DIGITAL FILTERS
- 6 APPLICATION OF COMPUTER NETWORKING USING NEURAL NETWORK
- 7 APPLICATION OF NEURAL NETWORKS IN OIL REFINERIES
- 8 INTRODUCTION TO FUZZY SETS: BASIC DEFINITIONS AND RELATIONS
- 9 INTRODUCTION TO FUZZY LOGIC
- 10 FUZZY CONTROL AND STABILITY
- 11 SOFT COMPUTING APPROACH TO SAFE NAVIGATION OF AUTONOMOUS PLANETARY ROVERS
- 12 AUTONOMOUS UNDERWATER VEHICLE CONTROL USING FUZZY LOGIC
- 13 APPLICATION OF FUZZY
- 14 APPLICATION OF ADAPTIVE NEURO-FUZZY INFERENCE SYSTEMS TO ROBOTICS
- 15 APPLICATION OF SOFT COMPUTING FOR DESALINATION TECHNOLOGY
- 16 COMPUTATIONAL INTELLIGENCE APPROACH TO OBJECT RECOGNITION
- 17 AN INTRODUCTION TO EVOLUTIONARY COMPUTATION
- 18 EVOLUTIONARY CONCEPTS FOR IMAGE PROCESSING APPLICATIONS
- 19 EVOLUTIONARY FUZZY SYSTEMS
- 20 GENETIC AND EVOLUTIONARY METHODS FOR MOBILE ROBOT MOTION CONTROL AND PATH PLANNING
- 21 PROBLEMS AND MATLAB PROGRAMS
- INDEX