Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems

Shakiba Yaghoubi, Georgios Fainekos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

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 languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages529-534
Number of pages6
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Other

Other2017 American Control Conference, ACC 2017
CountryUnited States
CitySeattle
Period5/24/175/26/17

Fingerprint

Nonlinear systems
Specifications
Global optimization
Engineers

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Yaghoubi, S., & Fainekos, G. (2017). Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems. In 2017 American Control Conference, ACC 2017 (pp. 529-534). [7963007] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2017.7963007

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.

Research output: Chapter in Book/Report/Conference proceedingConference 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, 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
Yaghoubi S, Fainekos G. Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems. In 2017 American Control Conference, ACC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 529-534. 7963007 https://doi.org/10.23919/ACC.2017.7963007
Yaghoubi, Shakiba ; Fainekos, Georgios. / Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems. 2017 American Control Conference, ACC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 529-534
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