Includes bibliographical references (p. 312-315) and index.
|Statement||Dimitri P. Bertsekas and Steven E. Shreve.|
|Series||Optimization and neural computation series|
|Contributions||Shreve, Steven E.|
|LC Classifications||T57.83 .B49 1996|
|The Physical Object|
|Pagination||xiii, 323 p. ;|
|Number of Pages||323|
|LC Control Number||96080191|
Apr 21, · Stochastic Optimal Control (SOC)―a mathematical theory concerned with minimizing a cost (or maximizing a payout) pertaining to a controlled dynamic process under uncertainty―has proven incredibly helpful to understanding and predicting debt crises and evaluating proposed financial regulation and risk rajasthan-travel-tour.com by: Stochastic Optimal Control: The Discrete-Time Case (Optimization and Neural Computation Series) 1st Edition by Dimitri P. Bertsekas (Author)Cited by: Further, it establishes the theory of and methods for stochastic optimal control of randomly-excited engineering structures in the context of probability density evolution methods, such as physically-based stochastic optimal (PSO) control. By logically integrating randomness into control gain, the book helps readers design elegant control. This book gathers the most essential results, including recent ones, on linear-quadratic optimal control problems, which represent an important aspect of stochastic control. The results are introduced in the context of finite and infinite horizon problems, and for two .
This book proposes the basic formulation for structural performance control with an account of stochastic dynamics induced by engineering excitations in the nature of non-stationary and non-Gaussian processes and implements the reliability-based stochastic optimal control of structures. Stochastic Optimal Control: The Discrete-Time Case Dimitri P. Bertsekas and Steven E. Shreve This book was originally published by Academic Press in , and republished by Athena Scientific in in paperback form. Kibzun A and Ignatov A () On the existence of optimal strategies in the control problem for a stochastic discrete time system with respect to the probability criterion, Automation and Remote Control, , (), Online publication date: 1-Oct Dec 11, · Introduction to Stochastic Control Theory and millions of other books are available for Amazon Kindle. Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device rajasthan-travel-tour.com by:
In these notes, I give a very quick introduction to stochastic optimal control and the dynamic programming approach to control. This is done through several important examples that arise in mathematical ﬁnance and economics. The theory of viscosity solutions of Crandall and Lions is also demonstrated in one example. This will be our control, and is subject to the obvious constraint that 0 ≤ α(t) ≤ 1 for each time t≥ 0. Given such a control, the corresponding dynamics are provided by the ODE ˆ x˙(t) = kα(t)x(t) x(0) = x0. the constant k>0 modelling the growth rate of our reinvestment. Stochastic Optimal Control of Structures Yongbo Peng, Jie Li This book proposes, for the first time, a basic formulation for structural control that takes into account the stochastic dynamics induced by engineering excitations in the nature of non-stationary and non-Gaussian processes. “This book addresses a comprehensive study of the theory of stochastic optimal control when the underlying dynamic evolves as a stochastic differential equation in infinite dimension. It contains the most general models appearing in the literature and at the same time provides interesting rajasthan-travel-tour.com: $