Stochastic approximations of hybrid systems with continuous flow maps

被引：0

作者：

Teel, Andrew R. ^{[1
]}

Goebel, Rafal ^{[2
]}

机构：

[1] Univ Calif Santa Barbara, Elect & Comp Engn Dept, Santa Barbara, CA 93106 USA

[2] Loyola Univ Chicago, Dept Math & Stat, Chicago, IL 60660 USA

来源：

IFAC PAPERSONLINE | 2024年 / 58卷 / 11期

关键词：

Hybrid systems; stochastic systems; simulation; CONVERGENCE; INCLUSIONS;

D O I：

10.1016/j.ifacol.2024.07.438

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We consider the behavior of stochastic simulators of non-stochastic hybrid systems. We focus on the case where the simulator uses randomness to approximate a (non-stochastic) flow map. The latter is assumed to be a function that is continuous, or globally Lipschitz, for simplicity. Sufficient conditions guaranteeing that the sample paths of solutions to the simulator converge graphically, almost surely as the step size shrinks to zero, to solutions of a corresponding non-stochastic "average" hybrid system are provided. Probabilistic guarantees of closeness on compact time domains are also provided. Copyright (c) 2024 The Authors.

引用

页码：141 / 146

页数：6

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