Probabilistic design of a robust state-feedback controller based on parameter-dependent Lyapunov functions

被引:0
|
作者
Oishi, Y [1 ]
机构
[1] Univ Tokyo, Dept Math Informat, Bunkyo Ku, Tokyo 1138656, Japan
来源
42ND IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-6, PROCEEDINGS | 2003年
关键词
randomized algorithms; parameter-dependent Lyapunov functions; reduction of conservatism; parameter-dependent linear matrix inequalities; computational complexity;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An ellipsoid-based randomized algorithm of Kanev et at. is extended for the use of parameter-dependent Lyapunov functions. The proposed algorithm is considered to be useful for a less conservative design of a robust state-feedback controller against nonlinear parametric uncertainty. Indeed, it enables us to avoid polytopic overbounding of uncertainty and employment of parameter-independent Lyapunov functions. After a bounded number of iterations, the proposed algorithm gives with high confidence a probabilistic solution that satisfies a provided inequality for a high percentage of parameters. This algorithm can be used also for finding an optimal solution in an approximated sense. Convergence to a non-strict deterministic solution is considered and, especially, the expected number of iterations necessary to achieve a non-strict deterministic solution is proved to be infinite under some assumptions. A numerical example is provided.
引用
收藏
页码:1920 / 1925
页数:6
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