Numerical solution of the finite horizon stochastic linear quadratic control problem
Artikel i vetenskaplig tidskrift, 2017

The treatment of the stochastic linear quadratic optimal control problem with finite time horizon requires the solution of stochastic differential Riccati equations. We propose efficient numerical methods, which exploit the particular structure and can be applied for large-scale systems. They are based on numerical methods for ordinary differential equations such as Rosenbrock methods, backward differentiation formulas, and splitting methods. The performance of our approach is tested in numerical experiments.

splitting methods

stochastic LQR problem

stochastic Riccati equations

Rosenbrock methods

BDF methods


T. Damm

Technische Universität Kaiserslautern

H. Mena

Yachay Tech

University of Innsbruck

Tony Stillfjord

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Numerical Linear Algebra with Applications

1070-5325 (ISSN)

Vol. 24