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Stochastic Spline-Collocation Method for Constrained Optimal Control Problem Governed by Random Elliptic PDE

Gong, Benxue, Ge, Liang, Sun, Tongjun, Shen, Wanfang, Liu, Wenbin (2017) Stochastic Spline-Collocation Method for Constrained Optimal Control Problem Governed by Random Elliptic PDE. International Journal of Numerical Analysis and Modeling, 14 (4-5). pp. 627-645. ISSN 1705-5105.

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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.

Item Type: Article
Uncontrolled keywords: Random elliptic PDE, priori error estimates, stochastic spline-collocation method, Smolyak approximation, optimal control problem, deterministic constrained control
Divisions: Faculties > Social Sciences > Kent Business School
Depositing User: Steve Wenbin Liu
Date Deposited: 16 Aug 2017 15:17 UTC
Last Modified: 29 May 2019 19:22 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/62863 (The current URI for this page, for reference purposes)
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