Numerical solution of the finite horizon stochastic linear quadratic control problem |
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| Authors: | Tobias Damm Hermann Mena Tony Stillfjord |
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| Affiliation: | 1. Department of Mathematics, Technische Universit?t Kaiserslautern, Kaiserslautern, Germany;2. Institut Für Mathematik, Universit?t Innsbruck, Innsbruck, Austria;3. School of Mathematical Sciences and Information Technology, Yachay Tech, Urcuquí, Ecuador;4. Mathematical Sciences, Chalmers University of Technology and the University of Gothenburg, G?teborg, Sweden |
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| Abstract: | 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. |
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| Keywords: | BDF methods Rosenbrock methods splitting methods stochastic LQR problem stochastic Riccati equations |
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