Editorial Review:
In recent years there has been a wide interest in non-linear
adaptive control using approximate models, either for tracking or regulation,
and usually under the banner of neural network based control. The authors
present a unique critical evaluation of the approximate model philosophy and its
setting, rigorously comparing the performance of such controls against competing
designs. Analyzing a very topical aspect of contemporary research and control
practice this book highlights the situations in which approximate model based
designs are most appropriate and indicates scenarios in which other designs
could be used more productively. Throughout the text concepts are illustrated
using a variety of examples, both academic problems and those based on physical
examples. The work is designed to open the door to realistic applications.
- Unified coverage of the theory and application of a wide range of control
systems areas including neural network based control and control using the
approximate model
- Presents a mathematically well founded introduction to the area of
intelligent control
- A varied selection of practical examples drawn from a variety of fields,
including robotics and aerospace, illustrate theoretical principles
- Clear comparisons of a variety of control designs
- Cross disciplinary approach to this leading edge topic
A valuable reference for control practitioners and theorists, artificial
intelligence researchers and applied mathematicians, as well as graduate
students and researchers with an interest in adaptive control and stability.
Reviews from Wiley's Website ([link])
"I was attracted by this proposal. It is a relatively new area, the authors are well-respected, the book should make a useful contribution to the literature, and will have a reasonable 'shelf life'....There is no book at present taking their approach.", -- David Clarke, Professor of , University of Oxford, UK
"It would be a useful contribution to the literature.....I can see it as a useful reference book for graduate students and researchers working on related areas.",--Jing Sun, , Ford
"This is a difficult but important area of research. The book might be of interest to both non-linear and adaptive control theorists but also to people who work on control via neural networks....the fact that it builds upon the control designs in our book, which has sold well, might attract a part of its readership."--Professor Miroslav Krstic, , Department of Mechanical & Aerospace Engineering, University of California, San Diego, USA