Mathematical Control Theory for Stochastic Partial Differential Equations

lt;p>Qi Lü is a professor at School of Mathematics, Sichuan University, Chengdu, China. He is currently an associate editor/editorial board member of several journals including Systems & Control Letters.  His research interests include control theory for deterministic and stochastic partial differential equations and stochastic analysis.  

Xu Zhang is a Cheung Kong Scholar Distinguished Professor at School of Mathematics, Sichuan University, Chengdu, China. He is a sectional speaker at International Congress of Mathematicians (Control Theory & Optimization Section, 2010). He is/was the editor in chief/corresponding editor/associate editor for several journals including Mathematical Control and Related Fields, ESAIM: Control, Optimisation and Calculus of Variations, and SIAM Journal on Control and Optimization. His research interests include control theory, partial differential equations and stochastic analysis.   

1 Introduction.- 2 Some Preliminaries in Stochastic Calculus.- 3 Stochastic Evolution Equations.- 4 Backward Stochastic Evolution Equations.- 5 Control Problems in Stochastic Distributed Parameter Systems.- 6 Controllability for Stochastic Differential Equations in Finite Dimensions.- 7 Controllability for Stochastic Linear Evolution Equations.- 8 Exact Controllability for Stochastic Transport Equations.- 9 Controllability and Observability of Stochastic Parabolic Systems.- 10 Exact Controllability for a Refined Stochastic Wave Equation.- 11 Exact Controllability for Stochastic Schrödinger Equations.- 12 Pontryagin-Type Stochastic Maximum Principle.- 13 Linear Quadratic Optimal Control Problems.- References.- Index.

"This book of about 600 pages presents in an appealing manner how control theory can be applied for stochastic partial differential equations. I recommend it to all students and researchers interested in these topics." ( Gheorghe Tigan, zbMATH 1497.93001, 2022)

“This book of about 600 pages presents in an appealing manner how control theory can be applied for stochastic partial differential equations. I recommend it to all students and researchers interested in these topics.” (Gheorghe Tigan, zbMATH 1497.93001, 2022)