Linear-quadratic Control for Stochastic Equations in a Hilbert Space with Fractional Brownian Motions
Author(s) -
T. E. Duncan,
Bohdan Maslowski,
B. Pasik-Duncan
Publication year - 2012
Publication title -
siam journal on control and optimization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.486
H-Index - 116
eISSN - 1095-7138
pISSN - 0363-0129
DOI - 10.1137/110831416
Subject(s) - mathematics , stochastic control , linear quadratic gaussian control , stochastic partial differential equation , optimal control , stochastic differential equation , hilbert space , covariance , linear quadratic regulator , adjoint equation , noise (video) , mathematical analysis , partial differential equation , mathematical optimization , computer science , statistics , artificial intelligence , image (mathematics)
A linear-quadratic control problem with a finite time horizon for some infinite-dimensional controlled stochastic differential equations driven by a fractional Gaussian noise is formulated and solved. The feedback form of the optimal control and the optimal cost are given explicitly. The optimal control is the sum of the well-known linear feedback control for the associated deterministic linear-quadratic control problem and a suitable prediction of the adjoint optimal system response to the future noise. The covariance of the noise as well as the control operator in the system equation can in general be unbounded, so the results can also be applied where the noise or the control are on the boundary of the domain or at discrete points in the domain. Some examples of controlled stochastic partial differential equations are given.
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