Linear Systems and Optimal Control (Springer Series in Information Sciences, 18)

Charles K. Chui et Guanrong Chen

ISBN 10: 3642647871 / ISBN 13: 9783642647871

Edité par Springer, 2014

A propos de cet article

Ancien livre de bibliothèque. Traces d'usure sur la couverture. Couverture différente. Edition 2014. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Signs of wear on the cover. Different cover. Edition 2014. Ammareal gives back up to 15% of this item's net price to charity organizations.

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Détails bibliographiques

• Titre: Linear Systems and Optimal Control (Springer Series in Information Sciences, 18)
• Éditeur: Springer
• Date de parution: 2014
• Langue: anglais
• ISBN à 10 chiffres: 3642647871
• ISBN à 13 chiffres: 9783642647871
• Reliure: Softcover
• État de l'article: Bon

A propos de ce titre

Synopsis

A knowledge of linear systems provides a firm foundation for the study of optimal control theory and many areas of system theory and signal processing. State-space techniques developed since the early sixties have been proved to be very effective. The main objective of this book is to present a brief and somewhat complete investigation on the theory of linear systems, with emphasis on these techniques, in both continuous-time and discrete-time settings, and to demonstrate an application to the study of elementary (linear and nonlinear) optimal control theory. An essential feature of the state-space approach is that both time-varying and time-invariant systems are treated systematically. When time-varying systems are considered, another important subject that depends very much on the state-space formulation is perhaps real-time filtering, prediction, and smoothing via the Kalman filter. This subject is treated in our monograph entitled "Kalman Filtering with Real-Time Applications" published in this Springer Series in Information Sciences (Volume 17). For time-invariant systems, the recent frequency domain approaches using the techniques of Adamjan, Arov, and Krein (also known as AAK), balanced realization, and oo H theory via Nevanlinna-Pick interpolation seem very promising, and this will be studied in our forthcoming monograph entitled "Mathematical Ap- proach to Signal Processing and System Theory". The present elementary treatise on linear system theory should provide enough engineering and mathe- of these two subjects.