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147,79 €
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Linear Systems and Optimal Control
Linear Systems and Optimal Control
133,01
147,79 €
  • We will send in 10–14 business days.
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…
147.79
  • Publisher:
  • Year: 2014
  • Pages: 155
  • ISBN-10: 3642647871
  • ISBN-13: 9783642647871
  • Format: 15.6 x 23.4 x 0.9 cm, minkšti viršeliai
  • Language: English
  • SAVE -10% with code: EXTRA

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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.

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  • Author: Charles K Chui
  • Publisher:
  • Year: 2014
  • Pages: 155
  • ISBN-10: 3642647871
  • ISBN-13: 9783642647871
  • Format: 15.6 x 23.4 x 0.9 cm, minkšti viršeliai
  • Language: English English

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.

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