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Unbounded-time analysis of guarded LTI systems with inputs by abstract acceleration

Abstract:
Linear Time Invariant (LTI) systems are ubiquitous in software systems and control applications. Unbounded-time reachability analysis that can cope with industrial-scale models with thousands of variables is needed. To tackle this general problem, we use abstract acceleration, a method for unbounded-time polyhedral reachability analysis for linear systems. Existing variants of the method are restricted to closed systems, i.e., dynamical models without inputs or non-determinism. In this paper, we present an extension of abstract acceleration to linear loops with inputs, which correspond to discrete-time LTI control systems, and further study the interaction with guard conditions. The new method relies on a relaxation of the solution of the linear dynamical equation that leads to a precise over-approximation of the set of reachable states, which are evaluated using support functions. In order to increase scalability, we use floating-point computations and ensure soundness by interval arithmetic. Our experiments show that performance increases by several orders of magnitude over alternative approaches in the literature. In turn, this tremendous speedup allows us to improve on precision by computing more expensive abstractions. We outperform state-of-the-art tools for unbounded-time analysis of LTI system with inputs in speed as well as in precision.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-662-48288-9_18

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Institution:
University of Oxford
Oxford college:
Linacre College
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author

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Role:
Editor
Role:
Editor


Publisher:
Springer
Host title:
Lecture Notes in Computer Science: SAS 2015: Static Analysis
Journal:
Lecture Notes in Computer Science: SAS 2015: Static Analysis More from this journal
Volume:
9291
Pages:
312-331
Publication date:
2015-01-01
DOI:
ISSN:
0302-9743 and 1611-3349
ISBN:
9783662482872


Keywords:
Pubs id:
pubs:527448
UUID:
uuid:a97af922-4921-4b77-8c7b-b229fee3b00a
Local pid:
pubs:527448
Source identifiers:
527448
Deposit date:
2017-01-28

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