Neuro-adaptive process control : a practical approach
著者
書誌事項
Neuro-adaptive process control : a practical approach
Wiley, c1996
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
There is a substantial interest in the perceived benefits of using neural networks techniques to improve the performance of control systems in industrial plants. This is a relatively new approach to control engineering and the field is developing rapidly. This book focuses on two practical approaches to increasing the efficiency level of process plants by exploiting the adaptive characteristics of neural networks to their full potential.
目次
- Wide Operating Range Control
- An Existing Approach
- Artificial Neural Networks
- Purpose of this Book
- Outline of this Book
- Background: Historical Perspective
- Neural Networks
- Identification and Control
- History-Stack Adaptation and Identification: Motivation
- History-Stack Adaptation Algorithm
- Some Characteristics of HSA
- Algorithm Extensions
- Neural Network Model Design
- Simulated Conical Tank Example
- Additional Tests - Tank Example
- A Composite Non-Linear Example
- Neural Network Topology Tests
- Reinforcement Learning Control: Reinforcement Back-Propagation
- Gradient-Based RBP Algorithm
- Optimal Learned Performance Algorithm Theory
- OLP Demonstrations
- Adaptive Neural Model Control: ANMC Theory
- Non-Linear Tank Level Control
- Adaptive Multivariable Control of an Evaporator
- Practical Aspects and Demonstration: pH Control
- Experimental pH plant
- Software and Instrumentation
- Plant Characteristics
- ANMC Configuration
- ANMC Test Results
- Test Results
- Test Results for Other Control Methods
- The Final Word.
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