Readings Newsletter
Become a Readings Member to make your shopping experience even easier.
Sign in or sign up for free!
You’re not far away from qualifying for FREE standard shipping within Australia
You’ve qualified for FREE standard shipping within Australia
The cart is loading…
This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This monograph presents a detailed and unified treatment of the theory of reduced order systems. Topics include reduced order modeling, reduced order estimation, reduced order control, and the design of reduced order compensators for stochastic systems.
Special emphasis is placed on optimization using a quadratic performance criterion. Both continuous and discrete time linear dynamical systems are considered, and state space system representation is used throughout.
$9.00 standard shipping within Australia
FREE standard shipping within Australia for orders over $100.00
Express & International shipping calculated at checkout
This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This monograph presents a detailed and unified treatment of the theory of reduced order systems. Topics include reduced order modeling, reduced order estimation, reduced order control, and the design of reduced order compensators for stochastic systems.
Special emphasis is placed on optimization using a quadratic performance criterion. Both continuous and discrete time linear dynamical systems are considered, and state space system representation is used throughout.