This paper proposes a novel finite volume element (FVE) scheme for linear parabolic optimal control problems (OCPs) subject to integral control constraints. The state and co-state variables were approximated using continuous piecewise linear finite elements, while the control variable was discretized via piecewise constant functions. First, following the discretize-then-optimize approach, the FVE approximation of the parabolic OCP was formulated. Second, the first-order optimality conditions were derived, and corresponding error estimates in the $ L^2(J; H^1(\Omega)) $-norm for the state and co-state variables, as well as in the $ L^2(J; L^2(\Omega)) $-norm for the control variable, were established. These estimates quantify the deviation between the discrete solutions and the exact solutions over the time interval $ J $ and spatial domain $ \Omega $, providing rigorous bounds on the approximation errors. Third, some superclose results between the projection of the exact solution and the discrete solution for all variables were analyzed, leading to optimal-order error estimates in the $ L^\infty(J; L^2(\Omega)) $-norm for all variables. Finally, a numerical example was presented to validate the theoretical results. We believe that this is the first article to construct an FVE approximation based on the discretize-then-optimize approach for the parabolic OCP.
Citation: Chunjuan Hou, Baitong Ma. Finite volume element discretization of optimal control of the parabolic equation using the discretize-then-optimize approach[J]. AIMS Mathematics, 2026, 11(1): 444-461. doi: 10.3934/math.2026019
This paper proposes a novel finite volume element (FVE) scheme for linear parabolic optimal control problems (OCPs) subject to integral control constraints. The state and co-state variables were approximated using continuous piecewise linear finite elements, while the control variable was discretized via piecewise constant functions. First, following the discretize-then-optimize approach, the FVE approximation of the parabolic OCP was formulated. Second, the first-order optimality conditions were derived, and corresponding error estimates in the $ L^2(J; H^1(\Omega)) $-norm for the state and co-state variables, as well as in the $ L^2(J; L^2(\Omega)) $-norm for the control variable, were established. These estimates quantify the deviation between the discrete solutions and the exact solutions over the time interval $ J $ and spatial domain $ \Omega $, providing rigorous bounds on the approximation errors. Third, some superclose results between the projection of the exact solution and the discrete solution for all variables were analyzed, leading to optimal-order error estimates in the $ L^\infty(J; L^2(\Omega)) $-norm for all variables. Finally, a numerical example was presented to validate the theoretical results. We believe that this is the first article to construct an FVE approximation based on the discretize-then-optimize approach for the parabolic OCP.
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