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Intelligent Control Systems Using Soft Computing Methodologies



This book is about intelligent control systems and how to use soft computing methodologies to create them. It starts with an overview of different control methodologies and how they work, and then moves on to different implementations of neural networks and fuzzy logic. It finishes with a discussion of genetic algorithms and how to integrate them into soft computing methodologies. more details
Key Features:
  • Provides an overview of different control methodologies and how they work
  • Provides implementations of neural networks and fuzzy logic
  • Discusses genetic algorithms and how to integrate them into soft computing methodologies


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Features
Author Mo Jamshidi
Format Hardcover
ISBN 9780849318757
Publisher CRC Press Inc
Manufacturer Crc Press Inc
Description
This book is about intelligent control systems and how to use soft computing methodologies to create them. It starts with an overview of different control methodologies and how they work, and then moves on to different implementations of neural networks and fuzzy logic. It finishes with a discussion of genetic algorithms and how to integrate them into soft computing methodologies.

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. Suited as both a textbook and 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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