Mathematical Control Theory for Stochastic Partial Differential Equations (Hardcover, 1st ed. 2021)

This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory. The new phenomena and difficulties arising in the study of controllability and optimal control problems for this type of system are explained in detail. Interestingly enough, one has to develop new mathematical tools to solve some problems in this field, such as the global Carleman estimate for stochastic partial differential equations and the stochastic transposition method for backward stochastic evolution equations. In a certain sense, the stochastic distributed parameter control system is the most general control system in the context of classical physics. Accordingly, studying this field may also yield valuable insights into quantum control systems. A basic grasp of functional analysis, partial differential equations, and control theory for deterministic systems is the only prerequisite for reading this book.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Probability Theory and Stochastic Modelling, 101
Release date:	September 2021
First published:	2021
Authors:	Qi Lu • Xu Zhang
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	592
Edition:	1st ed. 2021
ISBN-13:	978-3-03-082330-6
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Differential equations Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Calculus of variations Promotions
LSN:	3-03-082330-X
Barcode:	9783030823306

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