This book introduces the fundamental ideas of linear stochastic estimation or what is more commonly known as optimal estimation. These ideas are important in the field of control where the signals received are noisy and used to determine the flight path of a plane, orbit of a space vehicle or the co
Optimal estimation of dynamic systems
โ Scribed by John L. Crassidis, John L. Junkins
- Publisher
- Chapman & Hall/CRC
- Year
- 2004
- Tongue
- English
- Leaves
- 599
- Series
- Chapman & Hall Crc Applied Mathematics & Nonlinear Science volume 2
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Most newcomers to the field of linear stochastic estimation go through a difficult process in understanding and applying the theory.This book minimizes the process while introducing the fundamentals of optimal estimation.Optimal Estimation of Dynamic Systems explores topics that are important in the field of control where the signals received are used to determine highly sensitive processes such as the flight path of a plane, the orbit of a space vehicle, or the control of a machine. The authors use dynamic models from mechanical and aerospace engineering to provide immediate results of estimation concepts with a minimal reliance on mathematical skills. The book documents the development of the central concepts and methods of optimal estimation theory in a manner accessible to engineering students, applied mathematicians, and practicing engineers. It includes rigorous theoretial derivations and a significant amount of qualitiative discussion and judgements. It also presents prototype algorithms, giving detail and discussion to stimulate development of efficient computer programs and intelligent use of them.This book illustrates the application of optimal estimation methods to problems with varying degrees of analytical and numercial difficulty. It compares various approaches to help develop a feel for the absolute and relative utility of different methods, and provides many applications in the fields of aerospace, mechanical, and electrical engineering.
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Crassidis (mechanical and aerospace engineering, State University of New York-Buffalo) and Junkins (Center for Mechanics and Control, Texas A&M University) introduce fundamentals of estimation to engineers, scientists, applied mathematicians, and advanced students, using dynamic models from mechanic
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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