Mathematical Control Theory for Stochastic Partial Differential Equations (eBook)

Artikelnummer: 978-3-030-82331-3
Einband: PDF
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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.



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.



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VerlagSpringer Nature Switzerland
EinbandPDF
Erscheinungsjahr2021
Seitenangabe592 S.
AusgabekennzeichenEnglisch
AbbildungenXIII, 592 p.
Masse7'287 KB
PlattformPDF
ReiheProbability Theory and Stochastic Modelling; Mathematics and Statistics; Mathematics and Statistics
AutorLü, Qi / Zhang, Xu

Alle Bände der Reihe "Probability Theory and Stochastic Modelling; Mathematics and Statistics; Mathematics and Statistics (R0)"

Über den Autor Qi Lü

Qi Lü is a professor at School of Mathematics, Sichuan University, Chengdu, China. He is a sectional speaker at International Congress of Mathematicians (Control Theory and Optimization Section, 2022). He is currently an associate editor/editorial board member of several journals including SIAM Journal on Control and Optimization, ESAIM: Control, Optimisation and Calculus of Variations, Annals of Applied Probability and Systems & Control Letters. His research interests include inverse problems and control theory for deterministic and stochastic partial differential equations and stochastic analysis. Yu Wang is an assistant professor at School of Mathematics, Southwest Jiaotong University, Chengdu, China. His research interests include inverse problems and control theory for stochastic partial differential equations.

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