Volume 14, Issue 4-5
Stochastic Spline-Collocation Method for Constrained Optimal Control Problem Governed by Random Elliptic PDE.

Benxue Gong, Liang Ge, Tongjun Sun, Wanfang Shen & W.B. Liu

Int. J. Numer. Anal. Mod., 14 (2017), pp. 627-645

Published online: 2017-08

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  • Abstract

In this paper, we investigate a stochastic spline-collocation approximation scheme for an optimal control problem governed by an elliptic PDE with random field coefficients. We obtain the necessary and sufficient optimality conditions for the optimal control problem and establish a scheme to approximate the optimality system through the discretization with respect to the spatial space by finite elements method and the probability space by stochastic splinecollocation method. We further investigate Smolyak approximation schemes, which are effective collocation strategies for smooth problems that depend on a moderately large number of random variables. For more general control problems where the state may be non-smooth with respect to the random variables in some areas, we adopt a domain decomposition strategy to partition the random space into smooth and non-smooth parts and then apply Smolyak scheme and spline approximation respectively. A priori error estimates are derived for the state, the co-state and the control variables. Numerical examples are presented to illustrate our theoretical results.

  • Keywords

Random elliptic PDE priori error estimates stochastic spline-collocation method Smolyak approximation optimal control problem deterministic constrained control

  • AMS Subject Headings

65M55 65N30

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{IJNAM-14-627, author = {Benxue Gong, Liang Ge, Tongjun Sun, Wanfang Shen and W.B. Liu}, title = {Stochastic Spline-Collocation Method for Constrained Optimal Control Problem Governed by Random Elliptic PDE.}, journal = {International Journal of Numerical Analysis and Modeling}, year = {2017}, volume = {14}, number = {4-5}, pages = {627--645}, abstract = {In this paper, we investigate a stochastic spline-collocation approximation scheme for an optimal control problem governed by an elliptic PDE with random field coefficients. We obtain the necessary and sufficient optimality conditions for the optimal control problem and establish a scheme to approximate the optimality system through the discretization with respect to the spatial space by finite elements method and the probability space by stochastic splinecollocation method. We further investigate Smolyak approximation schemes, which are effective collocation strategies for smooth problems that depend on a moderately large number of random variables. For more general control problems where the state may be non-smooth with respect to the random variables in some areas, we adopt a domain decomposition strategy to partition the random space into smooth and non-smooth parts and then apply Smolyak scheme and spline approximation respectively. A priori error estimates are derived for the state, the co-state and the control variables. Numerical examples are presented to illustrate our theoretical results.}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/10053.html} }
TY - JOUR T1 - Stochastic Spline-Collocation Method for Constrained Optimal Control Problem Governed by Random Elliptic PDE. AU - Benxue Gong, Liang Ge, Tongjun Sun, Wanfang Shen & W.B. Liu JO - International Journal of Numerical Analysis and Modeling VL - 4-5 SP - 627 EP - 645 PY - 2017 DA - 2017/08 SN - 14 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/ijnam/10053.html KW - Random elliptic PDE KW - priori error estimates KW - stochastic spline-collocation method KW - Smolyak approximation KW - optimal control problem KW - deterministic constrained control AB - In this paper, we investigate a stochastic spline-collocation approximation scheme for an optimal control problem governed by an elliptic PDE with random field coefficients. We obtain the necessary and sufficient optimality conditions for the optimal control problem and establish a scheme to approximate the optimality system through the discretization with respect to the spatial space by finite elements method and the probability space by stochastic splinecollocation method. We further investigate Smolyak approximation schemes, which are effective collocation strategies for smooth problems that depend on a moderately large number of random variables. For more general control problems where the state may be non-smooth with respect to the random variables in some areas, we adopt a domain decomposition strategy to partition the random space into smooth and non-smooth parts and then apply Smolyak scheme and spline approximation respectively. A priori error estimates are derived for the state, the co-state and the control variables. Numerical examples are presented to illustrate our theoretical results.
Benxue Gong, Liang Ge, Tongjun Sun, Wanfang Shen & W.B. Liu. (1970). Stochastic Spline-Collocation Method for Constrained Optimal Control Problem Governed by Random Elliptic PDE.. International Journal of Numerical Analysis and Modeling. 14 (4-5). 627-645. doi:
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