English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Computing tight over-approximation of reach sets of a controlled uncertaindynamical system is a common practice in verification of safety-criticalcyber-physical systems (CPS). While several algorithms are available for thispurpose, they tend to be computationally demanding in CPS applications sincehere, the computational resources such as processor availability tend to bescarce, time-varying and difficult to model. A natural idea then is to design"computation-aware" algorithms that can dynamically adapt with respect to theprocessor availability in a provably safe manner. Even though this idea shouldbe applicable in broader context, here we focus on ellipsoidalover-approximations. We demonstrate that the algorithms for ellipsoidalover-approximation of reach sets of uncertain linear systems, are well-suitedfor anytime implementation in the sense the quality of the over-approximationcan be dynamically traded off depending on the computational time available,all the while guaranteeing safety. We give a numerical example to illustratethe idea, and point out possible future directions.

Anytime Ellipsoidal Over-approximation of Forward Reach Sets of Uncertain Linear Systems