Robust Optimization-Directed Design

Andrew J. Kurdila (u. a.)

ISBN 10: 0387282637 / ISBN 13: 9780387282633

Published by Springer, 2005

About this Item

Robust Optimization-Directed Design | Andrew J. Kurdila (u. a.) | Buch | ix | Englisch | 2005 | Springer | EAN 9780387282633 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Seller Inventory # 102159274

Bibliographic Details

• Title: Robust Optimization-Directed Design
• Publisher: Springer
• Publication Date: 2005
• Language: English
• ISBN 10: 0387282637
• ISBN 13: 9780387282633
• Binding: Buch
• Condition: Neu
• Dimensions: 240W x 161H x 21D millimeters 240 millimeters width by 161 millimeters height by 21 millimeters depth
• Weight: 593 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Robust design―that is, managing design uncertainties such as model uncertainty or parametric uncertainty―is the often unpleasant issue crucial in much multidisciplinary optimal design work. Recently, there has been enormous practical interest in strategies for applying optimization tools to the development of robust solutions and designs in several areas, including aerodynamics, the integration of sensing (e.g., laser radars, vision-based systems, and millimeter-wave radars) and control, cooperative control with poorly modeled uncertainty, cascading failures in military and civilian applications, multi-mode seekers/sensor fusion, and data association problems and tracking systems. The contributions to this book explore these different strategies. The expression "optimization-directed” in this book’s title is meant to suggest that the focus is not agonizing over whether optimization strategies identify a true global optimum, but rather whether these strategies make significant design improvements.

From the Back Cover

Robust design―that is, managing design uncertainties such as model uncertainty or parametric uncertainty―is the often unpleasant issue crucial in much multidisciplinary optimal design work. Recently, there has been enormous practical interest in strategies for applying optimization tools to the development of robust solutions and designs in several areas, including aerodynamics, the integration of sensing (e.g., laser radars, vision-based systems, and millimeter-wave radars) and control, cooperative control with poorly modeled uncertainty, cascading failures in military and civilian applications, multi-mode seekers/sensor fusion, and data association problems and tracking systems. The contributions to this book explore these different strategies. The expression "optimization-directed” in this book’s title is meant to suggest that the focus is not agonizing over whether optimization strategies identify a true global optimum, but rather whether these strategies make significant design improvements.

 

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