A stochastic minimum principle and an adaptive pathwise algorithm for stochastic optimal control
Author(s)
Parpas, Panos; Webster, Mort
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We present a numerical method for finite-horizon stochastic optimal control models. We derive a stochastic minimum principle (SMP) and then develop a numerical method based on the direct solution of the SMP. The method combines Monte Carlo pathwise simulation and non-parametric interpolation methods. We present results from a standard linear quadratic control model, and a realistic case study that captures the stochastic dynamics of intermittent power generation in the context of optimal economic dispatch models.
Date issued
2013-04Department
Massachusetts Institute of Technology. Engineering Systems DivisionJournal
Automatica
Publisher
Elsevier
Citation
Parpas, Panos, and Mort Webster. “A Stochastic Minimum Principle and an Adaptive Pathwise Algorithm for Stochastic Optimal Control.” Automatica 49, no. 6 (June 2013): 1663–1671.
Version: Author's final manuscript
ISSN
00051098