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

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.

关键词： HJB equation optimal feedback control least-squares collocation method radial basis functions shape parameter adaptive method domain decomposition parallel computations

作者: H.Alwardi S.Wang L.S.Jennings

作者单位: Department of Mathematics, Nizwa College of Applied Sciences,P O Box 699, PC 611 Nizwa, Sultanate of School of Mathematics & Statistics, The University of Western Australia,35 Stirling Hwy, Crawley 600

会议类型: 国际会议

会议名称: 第8届国际最优化方法及应用大会

会议地点: 上海

会议语种:英文

页码: 164-165

在线出版日期: 2010-12-10（万方平台首次上网日期，不代表论文的发表时间）