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.
STOCHASTIC PROCESSES, ESTIMATION AND CONTROL.
Finite-dimensional linear estimation; Stochastic processes and linear estimation; Orthogonal increments processes; Estimation in dynamical systems; Linear stochastic control; An outline of further developments.
The book covers both state-space methods and those based on the polynomial approach. Similarities and differences between these approaches are highlighted.
A ‘stochastic’ process is a ‘random’ or ‘conjectural’ process, and this book is concerned with applied probability and statistics.
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.
This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand ...
A concise presentation which includes material on the application of time-sampling and spectra to a number of areas. It also includes detailed discussions of both Wierner-Kolmogorov theory and Kalman-Bucy theory....
This book provides a comprehensive presentation of classical and advanced topics in estimation and control of dynamical systems with an emphasis on stochastic control.
Stochastic Optimal Linear Estimation and Control
Stochastic Models: Estimation and Control: v. 2