Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems

Shakiba Yaghoubi; Georgios Fainekos

doi:10.23919/ACC.2017.7963007

Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems

Shakiba Yaghoubi, Georgios Fainekos

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Scopus citations

Abstract

Studying transient properties of nonlinear systems is an important problem for safety applications. Computationally, it is a very challenging problem to verify that a nonlinear system satisfies a safety specification. Therefore, in many cases, engineers try to solve a related problem, i.e., they try to find a system behavior that does not satisfy a given specification. This problem is called specification falsification. Optimization has been shown to be very effective in providing a practical solution to the falsification problem. In this paper, we provide effective and practical local and global optimization strategies to falsify a smooth nonlinear system of arbitrary complexity.

Original language	English (US)
Title of host publication	2017 American Control Conference, ACC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	529-534
Number of pages	6
ISBN (Electronic)	9781509059928
DOIs	https://doi.org/10.23919/ACC.2017.7963007
State	Published - Jun 29 2017
Event	2017 American Control Conference, ACC 2017 - Seattle, United States Duration: May 24 2017 → May 26 2017

Publication series

Name	Proceedings of the American Control Conference
ISSN (Print)	0743-1619

Other

Other	2017 American Control Conference, ACC 2017
Country/Territory	United States
City	Seattle
Period	5/24/17 → 5/26/17

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.23919/ACC.2017.7963007

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Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems. / Yaghoubi, Shakiba; Fainekos, Georgios.
2017 American Control Conference, ACC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 529-534 7963007 (Proceedings of the American Control Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yaghoubi, S & Fainekos, G 2017, Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems. in 2017 American Control Conference, ACC 2017., 7963007, Proceedings of the American Control Conference, Institute of Electrical and Electronics Engineers Inc., pp. 529-534, 2017 American Control Conference, ACC 2017, Seattle, United States, 5/24/17. https://doi.org/10.23919/ACC.2017.7963007

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abstract = "Studying transient properties of nonlinear systems is an important problem for safety applications. Computationally, it is a very challenging problem to verify that a nonlinear system satisfies a safety specification. Therefore, in many cases, engineers try to solve a related problem, i.e., they try to find a system behavior that does not satisfy a given specification. This problem is called specification falsification. Optimization has been shown to be very effective in providing a practical solution to the falsification problem. In this paper, we provide effective and practical local and global optimization strategies to falsify a smooth nonlinear system of arbitrary complexity.",

author = "Shakiba Yaghoubi and Georgios Fainekos",

note = "Funding Information: This work was partially supported by the NSF awards CNS-1319560 and IIP-1361926, and the NSF I/UCRC Center for Embedded Systems.; 2017 American Control Conference, ACC 2017 ; Conference date: 24-05-2017 Through 26-05-2017",

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AU - Fainekos, Georgios

N1 - Funding Information: This work was partially supported by the NSF awards CNS-1319560 and IIP-1361926, and the NSF I/UCRC Center for Embedded Systems.

PY - 2017/6/29

Y1 - 2017/6/29

N2 - Studying transient properties of nonlinear systems is an important problem for safety applications. Computationally, it is a very challenging problem to verify that a nonlinear system satisfies a safety specification. Therefore, in many cases, engineers try to solve a related problem, i.e., they try to find a system behavior that does not satisfy a given specification. This problem is called specification falsification. Optimization has been shown to be very effective in providing a practical solution to the falsification problem. In this paper, we provide effective and practical local and global optimization strategies to falsify a smooth nonlinear system of arbitrary complexity.

AB - Studying transient properties of nonlinear systems is an important problem for safety applications. Computationally, it is a very challenging problem to verify that a nonlinear system satisfies a safety specification. Therefore, in many cases, engineers try to solve a related problem, i.e., they try to find a system behavior that does not satisfy a given specification. This problem is called specification falsification. Optimization has been shown to be very effective in providing a practical solution to the falsification problem. In this paper, we provide effective and practical local and global optimization strategies to falsify a smooth nonlinear system of arbitrary complexity.

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ER -

Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems

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