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Compositional abstraction refinement for control synthesis
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-8167-3156
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-7309-8086
2018 (English)In: Nonlinear Analysis: Hybrid Systems, ISSN 1751-570X, E-ISSN 1878-7460, Vol. 27, p. 437-451Article in journal (Refereed) Published
Abstract [en]

This paper presents a compositional approach to specification-guided abstraction refinement for control synthesis of a nonlinear system associated with a method to over-approximate its reachable sets. Given an initial coarse partition of the state space, the control specification is given as a sequence of the cells of this partition to visit at each sampling time. The dynamics are decomposed into subsystems where some states and inputs are not observed, some states are observed but not controlled and where assume-guarantee obligations are used on the uncontrolled states of each subsystem. A finite abstraction is created for each subsystem through a refinement procedure starting from a coarse partition of the state space, then proceeding backwards on the specification sequence to iteratively split the elements of the partition whose coarseness prevents the satisfaction of the specification. Each refined abstraction is associated with a controller and it is proved that combining these local controllers can enforce the specification on the original system. The efficiency of the proposed approach compared to other abstraction methods is illustrated in a numerical example.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 27, p. 437-451
Keywords [en]
Symbolic control, Abstraction refinement, Compositional synthesis, Hybrid systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-215957DOI: 10.1016/j.nahs.2017.10.006ISI: 000417017100029Scopus ID: 2-s2.0-85034064467OAI: oai:DiVA.org:kth-215957DiVA, id: diva2:1150323
Funder
EU, Horizon 2020Swedish Foundation for Strategic Research Swedish Research CouncilKnut and Alice Wallenberg Foundation
Note

QC 20171213

Available from: 2017-10-18 Created: 2017-10-18 Last updated: 2017-12-22Bibliographically approved

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