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Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems
| dc.date.accessioned | 2021-11-04T15:39:43Z | |
| dc.date.available | 2021-11-04T15:39:43Z | |
| dc.date.issued | 2019-07 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/137349 | |
| dc.description.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. | en_US |
| dc.language.iso | en | |
| dc.publisher | Springer International Publishing | en_US |
| dc.relation.isversionof | 10.1007/978-3-030-25543-5_9 | en_US |
| dc.rights | Creative Commons Attribution 4.0 International license | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | Springer | en_US |
| dc.title | Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems | en_US |
| dc.type | Article | en_US |
| dc.identifier.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. | |
| dc.relation.journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2021-03-26T15:11:33Z | |
| dspace.orderedauthors | Gao, S; Kapinski, J; Deshmukh, J; Roohi, N; Solar-Lezama, A; Arechiga, N; Kong, S | en_US |
| dspace.date.submission | 2021-03-26T15:11:34Z | |
| mit.journal.volume | 11562 | en_US |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |
