Case Studies in Data-Driven Verification of Dynamical Systems
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How_Case studies.pdf
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1.14 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Kozarev, Alexandar
Topcu, Ufuk
How, Jonathan P
Quindlen, John Francis
Date Issued
April 2016
Journal
Proceedings of the 19th International Conference on Hybrid Systems: Computation and Control - HSCC '16
Publisher
Association for Computing Machinery (ACM)
Citation
Kozarev, Alexandar et al. “Case Studies in Data-Driven Verification of Dynamical Systems.” ACM Press, 2016. 81–86.
Version
Author's final manuscript
Abstract
We interpret several dynamical system verification questions, e.g., region of attraction and reachability analyses, as data classification problems. We discuss some of the tradeoffs between conventional optimization-based certificate constructions with certainty in the outcomes and this new date-driven approach with quantified confidence in the outcomes. The new methodology is aligned with emerging computing paradigms and has the potential to extend systematic verification to systems that do not necessarily admit closed-form models from certain specialized families. We demonstrate its effectiveness on a collection of both conventional and unconventional case studies including model reference adaptive control systems, nonlinear aircraft models, and reinforcement learning problems.
MIT Department
Massachusetts Institute of Technology. Aerospace Controls Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/2883817.2883846
