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An Adaptive Domain Decomposition Method for the Hamilton-Jacobi-Bellman Equation

机译:Hamilton-Jacobi-Bellman方程的自适应域分解方法

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摘要

In this paper, we propose an efficient algorithm for Hamilton-Jacobi-Bellman (HJB) equations governing a class of optimal feedback control problems. This algorithm is based on a non-overlapping domain decomposition method and an adaptive least-squares collocation radial basis function discretization with a novel matrix inversion technique. To demonstrate the accuracy and the effectiveness of this method, numerical experiments on test problems with up to three states and two control variables have been performed. The numerical results show that the proposed algorithm is a scalable parallel one and the computational costs decrease exponentially as the number of subdomains increases.
机译:在本文中,我们为控制一类最佳反馈控制问题的汉密尔顿-雅各比-贝尔曼(HJB)方程提出了一种有效的算法。该算法基于非重叠域分解方法和采用新型矩阵求逆技术的自适应最小二乘配置径向基函数离散化。为了证明这种方法的准确性和有效性,已经对多达三个状态和两个控制变量的测试问题进行了数值实验。数值结果表明,该算法是一种可扩展的并行算法,随着子域数量的增加,计算量呈指数下降。

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