Doubling Algorithm for Nonsymmetric Algebraic Riccati Equations Based on a Generalized Transformation
作者机构:School of Mathematics and Computational ScienceHunan Key Laboratory for Computation and Simulation in Science and EngineeringKey Laboratory of Intelligent Computing and Information Processing of Ministry of EducationXiangtan UniversityXiangtan 411105HunanChina School of ScienceHunan City UniversityYiyang 413000HunanChina School of ScienceHunan University of TechnologyZhuzhou 412000HunanChina
出 版 物:《Advances in Applied Mathematics and Mechanics》 (应用数学与力学进展(英文))
年 卷 期:2018年第10卷第6期
页 面:1327-1343页
核心收录:
学科分类:07[理学] 0701[理学-数学] 070101[理学-基础数学]
基 金:The work of B.Tang was supported partly by Hunan Provincial Innovation Foundation for Postgraduate(No.CX2016B249) Hunan Provincial Natural Science Foundation of China(No.2018JJ3019) The work of N.Dong was supported partly by the Hunan Provincial Natural Science Foundation of China(Nos.14JJ2114,2017JJ2071) the Excellent Youth Foundation and General Foundation of Hunan Educational Department(Nos.17B071,17C0466)
主 题:Shift-and-shrink transformation generalized Cayley transformation doubling algorithm nonsymmetric algebraic Riccati equation
摘 要:We consider computing the minimal nonnegative solution of the nonsymmetric algebraic Riccati equation with *** is well known that such equations can be efficiently solved via the structure-preserving doubling algorithm(SDA)with the shift-and-shrink transformation or the generalized Cayley *** this paper,we propose a more generalized transformation of which the shift-and-shrink transformation and the generalized Cayley transformation could be viewed as two special ***,the doubling algorithm based on the proposed generalized transformation is presented and shown to be ***,the convergence result and the comparison theorem on convergent rate are *** numerical experiments show that the doubling algorithm with the generalized transformation is efficient to derive the minimal nonnegative solution of nonsymmetric algebraic Riccati equation with M-matrix.