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Numerical solution of the finite horizon stochastic linear quadratic control problem

T. Damm ; H. Mena ; Tony Stillfjord (Institutionen för matematiska vetenskaper, Tillämpad matematik och statistik)
Numerical Linear Algebra with Applications (1070-5325). Vol. 24 (2017), 4,
[Artikel, refereegranskad vetenskaplig]

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.

Nyckelord: BDF methods, Rosenbrock methods, splitting methods, stochastic LQR problem, stochastic Riccati equations



Denna post skapades 2017-08-11. Senast ändrad 2017-08-11.
CPL Pubid: 251060

 

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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, Tillämpad matematik och statistikInstitutionen för matematiska vetenskaper, Tillämpad matematik och statistik (GU)

Ämnesområden

Matematik

Chalmers infrastruktur