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Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000003933581 | QA76.87 H79 1997 | Open Access Book | Book | Searching... |
Searching... | 30000005020080 | QA76.87 H79 1997 | Open Access Book | Advance Management | Searching... |
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Summary
Summary
A complete guide to the design and implementation of successful neurocontrol applications
Neurocontrol: Towards an Industrial Control Methodology is the first and only volume that presents a unified framework for neural network-based techniques. It demystifies neurocontroller design and promotes the broad application of neurocontrol to nonlinear control problems. Divided into two major parts --the theoretical and the practical --this book links neurocontrol with the concepts of classical control theory, describes the steps necessary to implement a working algorithm, and provides the information necessary to develop competitive applications of industrial size and complexity. Throughout, the focus is on the most important issues faced by control systems engineers working in this area, including
* Fundamental approaches to neurocontrol viewed as optimization tasks
* Neural network architectures for neurocontrol
* Learning algorithms viewed as optimization algorithms
* Identification of plant models from measured data
* Training of an optimal neurocontroller
* Robustness, adaptiveness, stability, and other special topics
* Implementation of neurocontrol applications
Supplemented with case studies of real-world industrial control applications --from car drive train control to wastewater treatment plant control --Neurocontrol is an important professional reference for control engineers in a wide range of industries as well as for automatic control and adaptive control researchers. It is also an excellent text for graduate and senior undergraduate students in neurocontrol and automatic control.
Author Notes
Tomas Hrycej is Senior Researcher at the Daimler-Benz Research Center in Ulm, Germany; former senior researcher at PCS Computer Systems in Munich; and the author of Modular Learning in Neural Networks. The case studies presented in this book are based on Dr. Hrycej's work at the Daimler-Benz Research Center.
Reviews 1
Choice Review
Neurocontrol is the latest evolving subfield of control. Classical control theory includes linear, nonlinear, fuzzy, optimal, robust, and adaptive techniques. Neurocontrol system implementations solve control problems by utilizing sampled data as input to numerical learning algorithms. Hrycej notes that neurocontrol can optimally solve a wide range of arbitrary, difficult, nonlinear control problems. He codifies its theory and practice in this first book ever on the subject, with the objective of providing in one source sufficient details to enable control researchers, theorists, and practitioners to develop and further apply this approach. The book features two major sections. The first, and longest, addresses the theory and concepts of neurocontrol. It builds on classical control theory and presents in a well-structured, readable format the key elements of neurocontrol theory. The second section describes four detailed case studies based on the author's experience to illustrate the application of the theory and scope of problems it may solve. Extensive reference list; brief index. Graduate students, faculty, and professionals. E. M. Aupperle University of Michigan
Table of Contents
| Methods |
| Important Concepts of Classical Control |
| Fundamental Approaches to Neurocontrol |
| Neural Networks for Control |
| Optimization Methods for Neurocontrol |
| Plant Identification |
| Controller Training |
| Robust Neurocontrol |
| Learning and Adaptiveness in Neurocontrol |
| Stability of Neurocontrollers |
| A Neurocontrol Algorithm_The Easiest Way to the Goal |
| Case Studies |
| Introductory Remarks to Case Studies |
| Elastomere Test Bench Control |
| Drive Train Test Bench Control |
| Lateral Control of an Autonomous Vehicle |
| Biological Wastewater Treatment Control |
| Conclusion: Application Potential of Neurocontrol |
| References |
| Index |
