Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems

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Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems

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Gao2019_Chapter_Numerically-RobustInductivePro.pdf

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Date Issued

July 2019

Journal

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Publisher

Springer International Publishing

Citation

2019. "Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems." Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11562.

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Final published version

Abstract

© The Author(s) 2019. We formulate numerically-robust inductive proof rules for unbounded stability and safety properties of continuous dynamical systems. These induction rules robustify standard notions of Lyapunov functions and barrier certificates so that they can tolerate small numerical errors. In this way, numerically-driven decision procedures can establish a sound and relative-complete proof system for unbounded properties of very general nonlinear systems. We demonstrate the effectiveness of the proposed rules for rigorously verifying unbounded properties of various nonlinear systems, including a challenging powertrain control model.

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Creative Commons Attribution 4.0 International license

https://creativecommons.org/licenses/by/4.0/

Persistent DSpace Link

https://hdl.handle.net/1721.1/137349

DOI of Published Version

10.1007/978-3-030-25543-5_9