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Convergence analysis of the Max-Plus Finite Element Method for Solving Deterministic Optimal Control Problems

机译:求解确定性最佳控制问题的MAX-PLUS有限元方法的收敛性分析

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We consider the Max-Plus Finite Element Method for Solving Deterministic Optimal Control Problems, which is a max-plus analogue of the Petrov-Galerkin finite element method. This method, that we introduced in a previous work, relies on a max-plus variational formulation. The error in the sup-norm can be bounded from the difference between the value function and its projections on max-plus and minplus semimodules when the max-plus analogue of the stiffness matrix is exactly known. We derive here a convergence result in arbitrary dimension for approximations of the stiffness matrix relying on the Hamiltonian, and for arbitrary discretization grid. We show that for a class of problems, the error estimate is of order δ+Δx(δ)−1 or pδ+Δx(δ)−1, depending on the choice of the approximation, where δ and δx are, respectively, the time and space discretization steps. We give numerical examples in dimension 2.
机译:我们考虑解决确定性最佳控制问题的MAX-Plus有限元方法,这是Petrov-Galerkin有限元方法的MAX-Plus模拟。这种方法,我们在以前的工作中引入,依赖于最大和变分制。当刚度矩阵的MAX-Plus模拟恰恰知道时,Sup-Norm中的误差可以从值函数与其上的差值之间的差异界定。我们在这里导出了依赖于汉密尔顿人的刚度矩阵的近似的任意尺寸的收敛性,以及任意离散化网格。我们表明,对于一类问题,误差估计值是Δ+Δx(δ) -1 -1 / sup>或pΔ+Δx(δ) -1 ,具体取决于分别选择近似,其中Δ和Δx是时间和空间离散化步骤。我们在尺寸2中提供数值例子。

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