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Introduction to Stochastic Control Theory
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Product Details
Author:
Karl J. Åström
Format:
Paperback
Pages:
320
Publisher:
Dover Publications (January 6, 2006)
Language:
English
ISBN-13:
9780486445311
ISBN-10:
0486445313
Weight:
13.52oz
Dimensions:
5.5" x 8.5"
Case Pack:
26
Series:
Dover Books on Electrical Engineering
File:
Dover-Dover_09022026_P10562608_onix30_Complete-20260901.xml
Folder:
Dover
As low as:
$17.05
List Price:
$17.95
Publisher Identifier:
P-DOVER
Discount Code:
D
Audience:
College/higher education
Pub Discount:
65
Imprint:
Dover Publications
Overview
This text for upper-level undergraduates and graduate students explores stochastic control theory in terms of analysis, parametric optimization, and optimal stochastic control. Limited to linear systems with quadratic criteria, it covers discrete time as well as continuous time systems.
The first three chapters provide motivation and background material on stochastic processes, followed by an analysis of dynamical systems with inputs of stochastic processes. A simple version of the problem of optimal control of stochastic systems is discussed, along with an example of an industrial application of this theory. Subsequent discussions cover filtering and prediction theory as well as the general stochastic control problem for linear systems with quadratic criteria.
Each chapter begins with the discrete time version of a problem and progresses to a more challenging continuous time version of the same problem. Prerequisites include courses in analysis and probability theory in addition to a course in dynamical systems that covers frequency response and the state-space approach for continuous time and discrete time systems.
The first three chapters provide motivation and background material on stochastic processes, followed by an analysis of dynamical systems with inputs of stochastic processes. A simple version of the problem of optimal control of stochastic systems is discussed, along with an example of an industrial application of this theory. Subsequent discussions cover filtering and prediction theory as well as the general stochastic control problem for linear systems with quadratic criteria.
Each chapter begins with the discrete time version of a problem and progresses to a more challenging continuous time version of the same problem. Prerequisites include courses in analysis and probability theory in addition to a course in dynamical systems that covers frequency response and the state-space approach for continuous time and discrete time systems.
