Computational Effort of BDD-based Supervisor Synthesis of Extended Finite Automata

Abstract

DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

Efficiently enforcing mutual state exclusion requirements in symbolic supervisor synthesis

“…This synthesis algorithm is based on the algorithm introduced in [20]. The application of BDDs in this algorithm is studied in [21], [22]. We have split up the algorithm over multiple algorithms to enable reuse of parts later.…”

“…For symbolic supervisor synthesis, the computational effort can be expressed by peak used BDD nodes and BDD operation count [21]. The first metric is the maximal combined size of all BDDs during synthesis.…”

“…The BDD variable order and the order in which the edges are iterated over in the for loops have a large impact on the computational effort of a particular synthesis [21], [22]. The variable and edge order influence the synthesis efficiency that is found when comparing the two methods.…”

“…The efficiency of the method is evaluated by comparing the average results. Variable ordering heuristics FORCE and sliding window [21] are applied to the randomly generated variable orders, as this is the most realistic usage circumstance.…”

The Road Ahead for Supervisor Synthesis

“…Their sizes are very sensitive to the ordering of systems variables against which they are constructed. In [39], it was shown that the difference between the 'right' and 'wrong' ordering for the variables in Lock III can mean a shift in computation time from a few seconds to a few hours. Initial results show that ordering variables based on a DSM can yield a significant compaction of binary decision diagrams.…”