|
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook...
Product Description The technology of neural networks has attracted much attention in recent years. Their ability to learn nonlinear relationships is widely appreciated and is utilized in many different types of applications; modelling of dynamic systems, signal processing, and control system design being some of the most common. The theory of neural computing has matured considerably over the last decade and many problems of neural network design, training and evaluation have been resolved. This book provides a comprehensive introduction to the most popular class of neural network, the multilayer perceptron, and shows how it can be used for system identification and control. It aims to provide the reader with a sufficient theoretical background to understand the characteristics of different methods, to be aware of the pit-falls and to make proper decisions in all situations. The subjects treated include: System identification: multilayer perceptrons; how to conduct informative experiments; model structure selection; training methods; model validation; pruning algorithms. Control: direct inverse, internal model, feedforward, optimal and predictive control; feedback linearization and instantaneous-linearization-based controllers. Case studies: prediction of sunspot activity; modelling of a hydraulic actuator; control of a pneumatic servomechanism; water-level control in a conical tank. The book is very application-oriented and gives detailed and pragmatic recommendations that guide the user through the plethora of methods suggested in the literature. Furthermore, it attempts to introduce sound working procedures that can lead to efficient neural network solutions. This will make the book invaluable to the practitioner and as a textbook in courses with a significant hands-on component. Book Info Provides a comprehensive introduction to the most popular class of neural network, the multilayer perceptron, and shows how it can be used for system identification and control. Softcover. DLC: Neural networks (Computer science). Reader Reviews This is an excellent book. It contains theory and essential exaples for system identification and control based on ANN approach. The authors have also a WEB site where additional information and the toolboxes (MATLAB format) can be found. The programs work an they are easy to understand and run. I first tried the toolboxes (the user manuals are included with the toolboxes) and then ordered the book. It is worth having both. I highly recommend it, specially if you are a newbie in ANN but need a fast start. Cheers! Comment | | (Report this)
|
 |
|||
|
|||
|
|||
Current Page: engineeringbookmonster > Dynamic Systems and Control > Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook... Try the Arcspider search for hard to find Dynamic Systems and Control texts and references. Locate authoritative works by top researchers and authors in Dynamic Systems and Control and other science and engineering fields. Our database includes a huge collection of tools for the practicing engineer or student. Find the latest edition of a textbook, specification or an obscure periodical - and buy at a discount!
NOTE: All prices, specifications, and availability Copyright © 2008, engineeringbookmonster.com info@engineeringbookmonster.com Privacy Policy |
|||
