This book gathers the most essential results, including recent ones, on linear-quadratic optimal control problems, which represent an important aspect of stochastic control. It presents the results in the context of finite and infinite horizon problems, and discusses a number of new and interesting issues. Further, it precisely identifies, for the first time, the interconnections between three well-known, relevant issues - the existence of optimal controls, solvability of the optimality system, and solvability of the associated Riccati equation.�Although the content is largely self-contained, readers should have a basic grasp of linear algebra, functional analysis and stochastic ordinary differential equations.�The book is mainly intended for senior undergraduate and graduate students majoring�in applied mathematics who are interested in stochastic control theory. However, it will also appeal to researchers in other related areas, such as engineering, management, finance/economics and the social sciences.

N� de ref. del art�culo LU-9783030209216

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Detalles bibliogr�ficos

T�tulo: Stochastic Linear-Quadratic Optimal Control Theory: Open-Loop and Closed-Loop Solutions
Editor: Springer Nature Switzerland AG, CH
Fecha de publicaci�n: 2020
Idioma: Ingl�s
ISBN 10: 3030209210
ISBN 13: 9783030209216
Encuadernaci�n: Paperback
Edici�n: 1st ed. 2020.
Estado: New
Dimensiones: 15,5 cent�metros de ancho por 0,79 de alto por 23,5 de largo

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Sinopsis

This book gathers the most essential results, including recent ones, on linear-quadratic optimal control problems, which represent an important aspect of stochastic control. It presents the results in the context of finite and infinite horizon problems, and discusses a number of new and interesting issues. Further, it precisely identifies, for the first time, the interconnections between three well-known, relevant issues – the existence of optimal controls, solvability of the optimality system, and solvability of the associated Riccati equation. Although the content is largely self-contained, readers should have a basic grasp of linear algebra, functional analysis and stochastic ordinary differential equations. The book is mainly intended for senior undergraduate and graduate students majoring in applied mathematics who are interested in stochastic control theory. However, it will also appeal to researchers in other related areas, such as engineering, management, finance/economics and the social sciences.

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Jingrui Sun received his PhD in Mathematics from the University of Science and Technology of China in 2015. From 2015 to 2017, he was a Postdoctoral Fellow at the Hong Kong Polytechnic University and then a Research Fellow at the National University of Singapore. From 2017 to 2018, he was a Visiting Assistant Professor at the University of Central Florida, USA. Since the spring of 2019, he has been an Assistant Professor at the Southern University of Science and Technology, China. Dr. Sun has broad interests in the area of control theory and its applications. Aside from his primary research on stochastic optimal control and differential games, he is exploring forward and backward stochastic differential equations, stochastic analysis, and mathematical finance.

Jiongmin Yong received his PhD from Purdue University in 1986 and is currently a Professor of Mathematics at the University of Central Florida, USA. His main research interests include stochastic control, stochastic differential equations, and optimal control of partial differential equations. Professor Yong has co-authored the following influential books: “Stochastic Control: Hamiltonian Systems and HJB Equations” (with X. Y. Zhou, Springer 1999), “Forward-Backward Stochastic Differential Equations and Their Applications” (with J. Ma, Springer 1999), and “Optimal Control Theory for Infinite-Dimensional Systems” (with X. Li, Birkhauser 1995). His current interests include time-inconsistent stochastic control problems.

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