Diffusion approximation and optimal stochastic control

被引:0
|
作者
Liptser, R [1 ]
Runggaldier, WJ
Taksar, M
机构
[1] Tel Aviv Univ, Dept Elect Syst, IL-69978 Tel Aviv, Israel
[2] Russian Acad Sci, Inst Informat Transmiss Problems, Moscow 101447, Russia
[3] Univ Padua, Dipartimento Matemat Pura & Applicata, I-35131 Padua, Italy
[4] SUNY Stony Brook, Dept Appl Math & Stat, Stony Brook, NY 11794 USA
关键词
stochastic control; stochastic differential equations; weak convergence; asymptotic optimality;
D O I
暂无
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper a stochastic control model is studied that admits a diffusion approximation. In the prelimit model the disturbances are given by noise processes of various types: additive stationary noise, rapidly oscillating processes, and discontinuous processes with large intensity for jumps of small size. We show that a feedback control that satisfies a Lipschitz condition and is delta -optimal for the limit model remains delta -optimal also in the prelimit model. The method of proof uses the technique of weak convergence of stochastic processes. The result that is obtained extends a previous work by the authors, where the limit model is deterministic.
引用
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页码:669 / 696
页数:28
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