Characterization of optimal feedback for stochastic linear quadratic control problems

Abstract One of the fundamental issues in Control Theory is to design feedback controls. It is well-known that, the purpose of introducing Riccati equations in the study of deterministic linear quadratic control problems is exactly to construct the desired feedbacks. To date, the same problem in the...

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Bibliographic Details
Main Authors: Qi Lü, Tianxiao Wang, Xu Zhang
Format: Article
Language:English
Published: SpringerOpen 2017-09-01
Series:Probability, Uncertainty and Quantitative Risk
Subjects:
Online Access:http://link.springer.com/article/10.1186/s41546-017-0022-7
Description
Summary:Abstract One of the fundamental issues in Control Theory is to design feedback controls. It is well-known that, the purpose of introducing Riccati equations in the study of deterministic linear quadratic control problems is exactly to construct the desired feedbacks. To date, the same problem in the stochastic setting is only partially well-understood. In this paper, we establish the equivalence between the existence of optimal feedback controls for the stochastic linear quadratic control problems with random coefficients and the solvability of the corresponding backward stochastic Riccati equations in a suitable sense. We also give a counterexample showing the nonexistence of feedback controls to a solvable stochastic linear quadratic control problem. This is a new phenomenon in the stochastic setting, significantly different from its deterministic counterpart.
ISSN:2367-0126