| _version_ |
1811084263163953152
|
| collection |
MIT
|
| description |
© 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.
|
| first_indexed |
2024-09-23T12:47:51Z
|
| format |
Article
|
| id |
mit-1721.1/137349
|
| institution |
Massachusetts Institute of Technology
|
| language |
English
|
| last_indexed |
2024-09-23T12:47:51Z
|
| publishDate |
2021
|
| publisher |
Springer International Publishing
|
| record_format |
dspace
|
| spelling |
mit-1721.1/1373492022-04-01T17:27:47Z Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems © 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. 2021-11-04T15:39:43Z 2021-11-04T15:39:43Z 2019-07 2021-03-26T15:11:33Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/137349 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. en 10.1007/978-3-030-25543-5_9 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Springer International Publishing Springer
|
| spellingShingle |
Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems
|
| title |
Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems
|
| title_full |
Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems
|
| title_fullStr |
Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems
|
| title_full_unstemmed |
Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems
|
| title_short |
Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems
|
| title_sort |
numerically robust inductive proof rules for continuous dynamical systems
|
| url |
https://hdl.handle.net/1721.1/137349
|