Optimal Estimation of Dynamic Systems

John L. Crassidis

ISBN 10: 1439839859 / ISBN 13: 9781439839850

Published by Taylor & Francis Ltd, 2011

About this Item

Series: Chapman & Hall/CRC Applied Mathematics & Nonlinear Science. Num Pages: 749 pages, 117 black & white illustrations, 40 black & white tables. BIC Classification: GPFC; PBW. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 164 x 243 x 38. Weight in Grams: 1210. . 2011. 2nd Edition. Hardcover. . . . .

Seller Inventory # V9781439839850

Bibliographic Details

• Title: Optimal Estimation of Dynamic Systems
• Publisher: Taylor & Francis Ltd
• Publication Date: 2011
• Language: English
• ISBN 10: 1439839859
• ISBN 13: 9781439839850
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: New

About this title

Synopsis

Optimal Estimation of Dynamic Systems, Second Edition highlights the importance of both physical and numerical modeling in solving dynamics-based estimation problems found in engineering systems. Accessible to engineering students, applied mathematicians, and practicing engineers, the text presents the central concepts and methods of optimal estimation theory and applies the methods to problems with varying degrees of analytical and numerical difficulty. Different approaches are often compared to show their absolute and relative utility. The authors also offer prototype algorithms to stimulate the development and proper use of efficient computer programs. MATLABŪ codes for the examples are available on the book’s website.

New to the Second EditionWith more than 100 pages of new material, this reorganized edition expands upon the best-selling original to include comprehensive developments and updates. It incorporates new theoretical results, an entirely new chapter on advanced sequential state estimation, and additional examples and exercises.

An ideal self-study guide for practicing engineers as well as senior undergraduate and beginning graduate students, the book introduces the fundamentals of estimation and helps newcomers to understand the relationships between the estimation and modeling of dynamical systems. It also illustrates the application of the theory to real-world situations, such as spacecraft attitude determination, GPS navigation, orbit determination, and aircraft tracking.

About the Author

John L. Crassidis, Ph.D., is a professor of mechanical and aerospace engineering and the associate director of the Center for Multisource Information Fusion at the University at Buffalo, State University of New York. He previously worked at Texas A&M University, the Catholic University of America, and NASA’s Goddard Space Flight Center, where he contributed to attitude determination and control schemes for numerous spacecraft missions.

John L. Junkins, Ph.D., is a distinguished professor of aerospace engineering and the founder and director of the Center for Mechanics and Control at Texas A&M University. In addition to his historical contributions in analytical dynamics and spacecraft GNC, Dr. Junkins and his team have designed, developed, and demonstrated several new electro-optical sensing technologies.