Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition

Frank L. Lewis

ISBN 10: 0849390087 / ISBN 13: 9780849390081

Edité par Taylor & Francis Inc, 2007

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New copy - Usually dispatched within 4 working days. 934. N° de réf. du vendeur B9780849390081

Détails bibliographiques

Titre : Optimal and Robust Estimation: With an ...

Éditeur : Taylor & Francis Inc

Date d'édition : 2007

Reliure : Hardback

Etat : New

Edition : 2ème Édition

A propos de ce titre

Synopsis :

Book by Lewis Frank L Xie Lihua Popa Dan

Présentation de l'éditeur:

More than a decade ago, world-renowned control systems authority Frank L. Lewis introduced what would become a standard textbook on estimation, under the title Optimal Estimation, used in top universities throughout the world. The time has come for a new edition of this classic text, and Lewis enlisted the aid of two accomplished experts to bring the book completely up to date with the estimation methods driving today's high-performance systems.

A Classic Revisited
Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition reflects new developments in estimation theory and design techniques. As the title suggests, the major feature of this edition is the inclusion of robust methods. Three new chapters cover the robust Kalman filter, H-infinity filtering, and H-infinity filtering of discrete-time systems.

Modern Tools for Tomorrow's Engineers
This text overflows with examples that highlight practical applications of the theory and concepts. Design algorithms appear conveniently in tables, allowing students quick reference, easy implementation into software, and intuitive comparisons for selecting the best algorithm for a given application. In addition, downloadable MATLAB® code allows students to gain hands-on experience with industry-standard software tools for a wide variety of applications.

This cutting-edge and highly interactive text makes teaching, and learning, estimation methods easier and more modern than ever.