Introducing readers to adaptive systems in a rigorous but elementary fashion, this text emphasizes the mainstream developments in adaptive control and signal processing of linear discrete time systems. A unified framework is developed whereby the reader can analyze and understand any adaptive system in the literature. The so-called equilibrium analysis facilitates an understanding of the limitations and potential of adaptive systems in a transparent fashion; while the behavioural approach to linear systems plays an essential role at some key points in the text. So-called universal controllers are presented in some detail. Each chapter is accompanied by exercises that aim to develop certain aspects of the theory, as well as to give the reader a better understanding of the actual behaviour of adaptive systems.
Adaptive Systems: An Introduction
and over one million other books are available for Amazon Kindle.
Learn more
FREE Two-Day Shipping for Students. Learn more |
| ||||||||||||||||||
Book Description
Special Offers and Product Promotions
- Buy $50 in qualifying physical textbooks, get $5 in Amazon MP3 Credit. Here's how (restrictions apply)
Editorial Reviews
Review
From the reviews:
"This book is intended to be a first introduction to the theory of adaptive systems for graduate students. It treats exclusively deterministic adaptive control in a discrete-time formulation…. The basic course material contained in Chapters 1, 2, 3, 4, 5, and 6 is supplemented with the presentation of more advanced problems and tools such as well-posedness of the control problem during adaptation (Chapter 7), averaging techniques for analysis of adaptive systems (Chapter 8), and global dynamical analysis of adaptive systems operating in a plant-model mismatch situation (Chapter 9)." —Mathematical Reviews
"The book is based on graduate courses taught by both authors and is intended as a text-book. Therefore it is self contained and only basic knowledge of linear algebra and ordinary differential equations is needed. … cover the basic theory of adaptive systems and can be used for a one trimester course. … The book is accompanied by many solved and unsolved exercises, two Maple procedures and a large bibliography." (EMS Newsletter, Issue 27, March, 1998)
Product Details
Would you like to update product info or give feedback on images?
|
More About the Author
Discover books, learn about writers, read author blogs, and more.
Customer Reviews
|
Share your thoughts with other customers:
|
||||||||||||||||||||||
|
Most Helpful Customer Reviews
3 of 4 people found the following review helpful:
3.0 out of 5 stars
A review,
This review is from: Adaptive Systems: An Introduction (Systems & Control: Foundations & Applications) (Hardcover)
This book is a well written introduction into the area of adaptive systems. The text is fairly readable and the results are well presented. I would say that the book reaches its aim of providing an introduction into the area.The best feature of the book is the chapter on Averaging Analysis for Adaptive Systems. Chapters 3-5 are quite good as well. My only gripe with the book is the small number of errors-typos and a reader would be well advised to check out the errata sheet available on one of the author's webpage (I forget with one). I would have no problem in recommending the book to a Phd student as an introduction into adaptive systems.
Share your thoughts with other customers: Create your own review
|
|
Inside This Book
(learn more)
First Sentence:
In this chapter we introduce the subject of this book at an informal and intuitive level. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
adaptive model reference control, zero model error, model reference control problem, adaptive pole placement algorithm, echo path estimate, unfalsified model, adaptive system behavior, adaptive pole assignment, model reference controller, self tuning property, nonminimal representation, pole placement control, universal controllers, averaging ideas, model matching problem, frozen system, controllable models, pole placement problem, adaptive stabilization, averaging approximation, regressor vector, adaptive control algorithm, using averaging techniques, time scale separation, filter representation Key Phrases - Capitalized Phrases (CAPs): (learn more)
Proof See Exercise, Proof Define, Proof Point, Proof Recall New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
In this chapter we introduce the subject of this book at an informal and intuitive level. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
adaptive model reference control, zero model error, model reference control problem, adaptive pole placement algorithm, echo path estimate, unfalsified model, adaptive system behavior, adaptive pole assignment, model reference controller, self tuning property, nonminimal representation, pole placement control, universal controllers, averaging ideas, model matching problem, frozen system, controllable models, pole placement problem, adaptive stabilization, averaging approximation, regressor vector, adaptive control algorithm, using averaging techniques, time scale separation, filter representation Key Phrases - Capitalized Phrases (CAPs): (learn more)
Proof See Exercise, Proof Define, Proof Point, Proof Recall New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 36
books:
See all 36 books this book cites
20
books
cite this book:
See all 20 books citing this book
- Adaptive Control by B. D. O. Anderson in Back Matter (1), Back Matter (2), and Back Matter (3)
- Differential Equations (with CD-ROM) by Paul Blanchard in Back Matter (1), and Back Matter (2)
- Stochastic Systems: Estimation, Identification and Adaptive Control (Prentice-Hall Information and System Sciences Series) by P.R. Kumar in Back Matter
- Linear Systems by Thomas Kailath in Back Matter
- Set-Valued Analysis (Systems & Control: Foundations & Applications) by Jean-Pierre Aubin in Back Matter
See all 36 books this book cites
- Adaptation and Learning in Control and Signal Processing 2001 (IFAC Proceedings Volumes) by S. Bittanti on page 465
- Least-Mean-Square Adaptive Filters (Adaptive and Learning Systems for Signal Processing, Communications and Control Series) by Simon Haykin on page 168
- High Performance Control (Systems & Control: Foundations & Applications) by Teng-Tiow Tay in Back Matter
- Open Problems in Mathematical Systems and Control Theory (Communications and Control Engineering) by Vincent D. Blondel on page 175
- Foundations of Deterministic and Stochastic Control (Systems & Control: Foundations & Applications) by Jon H. Davis in Back Matter
See all 20 books citing this book
Books on Related Topics
(learn more)
|
Tag this product(What's this?)Think of a tag as a keyword or label you consider is strongly related to this product.
Tags will help all customers organize and find favorite items. |
Customer Discussions
|
This product's forum
Active discussions in related forums
Search Customer Discussions
|
Related forums
|
