Book Description
Stochastic Models: Estimation and Control: v. 2
Author : Maybeck
Publisher : Academic Press
Page : 307 pages
File Size : 28,54 MB
Release : 1982-08-10
Category : Mathematics
ISBN : 0080956513
Stochastic Models: Estimation and Control: v. 2
Author : Maybeck
Publisher : Academic Press
Page : 445 pages
File Size : 47,71 MB
Release : 1979-07-17
Category : Mathematics
ISBN : 0080956505
Stochastic Models: Estimation and Control: v. 1
Author : Peter S. Maybeck
Publisher : Academic Press
Page : 311 pages
File Size : 34,23 MB
Release : 1982-08-25
Category : Mathematics
ISBN : 0080960030
This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.
Author : Peter S. Maybeck
Publisher :
Page : pages
File Size : 35,89 MB
Release : 2002
Category : Control theory
ISBN :
Author : Peter S. Maybeck
Publisher :
Page : 423 pages
File Size : 47,68 MB
Release : 1979
Category :
ISBN : 9780124110427
Author : Peter S. Maybeck
Publisher :
Page : 423 pages
File Size : 50,3 MB
Release : 1979
Category : Control theory
ISBN :
Author : Peter S. Maybeck
Publisher :
Page : pages
File Size : 35,42 MB
Release : 1982
Category :
ISBN : 9780124807020
Author : Peter S. Maybeck
Publisher :
Page : pages
File Size : 15,93 MB
Release : 2002
Category :
ISBN :
Author : Peter S. Maybeck
Publisher :
Page : pages
File Size : 32,16 MB
Release : 1979
Category : Control theory
ISBN :
Author : Jason L. Speyer
Publisher : SIAM
Page : 391 pages
File Size : 29,54 MB
Release : 2008-11-06
Category : Mathematics
ISBN : 0898716551
The authors provide a comprehensive treatment of stochastic systems from the foundations of probability to stochastic optimal control. The book covers discrete- and continuous-time stochastic dynamic systems leading to the derivation of the Kalman filter, its properties, and its relation to the frequency domain Wiener filter aswell as the dynamic programming derivation of the linear quadratic Gaussian (LQG) and the linear exponential Gaussian (LEG) controllers and their relation to HÝsubscript 2¨ and HÝsubscript Ýinfinity¨¨ controllers and system robustness. This book is suitable for first-year graduate students in electrical, mechanical, chemical, and aerospace engineering specializing in systems and control. Students in computer science, economics, and possibly business will also find it useful.