A stochastic minimum principle and an adaptive pathwise algorithm for stochastic optimal control

Joint Program Reprint • Journal Article
A stochastic minimum principle and an adaptive pathwise algorithm for stochastic optimal control
Parpas, P. and M. Webster (2013)
Automatica, 49(6): 1663–1671

Reprint 2013-21 [Download]

Abstract/Summary:

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.

© 2013 Elsevier Ltd.

Citation:

Parpas, P. and M. Webster (2013): A stochastic minimum principle and an adaptive pathwise algorithm for stochastic optimal control. Automatica, 49(6): 1663–1671 (http://dx.doi.org/10.1016/j.automatica.2013.02.053)
  • Joint Program Reprint
  • Journal Article
A stochastic minimum principle and an adaptive pathwise algorithm for stochastic optimal control

Parpas, P. and M. Webster

Automatica
2013-21
49(6): 1663–1671

Abstract/Summary: 

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.

© 2013 Elsevier Ltd.

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