A low-rank solution method for Riccati equations with indefinite quadratic terms

被引：0
|
作者：
Peter Benner
Jan Heiland
Steffen W. R. Werner
机构：
[1] Max Planck Institute for Dynamics of Complex Technical Systems,Faculty of Mathematics
[2] Otto von Guericke University,Courant Institute of Mathematical Sciences
[3] New York University,undefined
来源：
Numerical Algorithms | 2023年 / 92卷
关键词：
Algebraic Riccati equation; Large-scale sparse matrices; Low-rank approximation; Iterative numerical method;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Algebraic Riccati equations with indefinite quadratic terms play an important role in applications related to robust controller design. While there are many established approaches to solve these in case of small-scale dense coefficients, there is no approach available to compute solutions in the large-scale sparse setting. In this paper, we develop an iterative method to compute low-rank approximations of stabilizing solutions of large-scale sparse continuous-time algebraic Riccati equations with indefinite quadratic terms. We test the developed approach for dense examples in comparison to other established matrix equation solvers, and investigate the applicability and performance in large-scale sparse examples.
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收藏
页码：1083 / 1103
页数：20
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