文章基本信息

标题：Computation of Controlled Invariants for Nonlinear Systems: Application to Safe Neural Networks Approximation and Control ⁎
本地全文：下载
作者：Adnane Saoud ; Ricardo G. Sanfelice
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：5
页码：91-96
DOI：10.1016/j.ifacol.2021.08.480
语种：English
出版社：Elsevier
摘要：AbstractIn this paper, we consider the problem of computing multidimensional interval controlled invariants for nonlinear input-affine systems. We first present sufficient conditions for an interval to be controlled invariant. Then, we introduce the concept of local framers, based on which we present a sound algorithm to compute interval controlled invariants. Finally, we show how the proposed framework makes it possible to provide safety guarantees when using deep neural networks, either as a model or a controller of nonlinear systems. Illustrative examples are provided showing the merits of the proposed approach and its scalability properties.
关键词：KeywordsInvariancenonlinear systemsframersneural networks