NDLI: On the transparency of automata as discrete-event control specifications

Content Provider	IEEE Xplore Digital Library
Author	Manh Tung Pham Dhananjayan, A. Kiam Tian Seow
Copyright Year	2010
Description	Author affiliation: Division of Computing Systems, School of Computer Engineering, Nanyang Technological University, Republic of Singapore (Manh Tung Pham; Dhananjayan, A.; Kiam Tian Seow)
Abstract	The problem of maximizing the transparency of specification automata for discrete event systems (DES's) is investigated. In a transparent specification automaton, events that are irrelevant to the specification but can occur in the system are ‘hidden’ in self-loops. Different automata of the same specification on a DES can be associated with different sets of such irrelevant events; and any such automaton is said to be the most transparent if it has an irrelevant event set of maximal cardinality. The transparency maximization problem is theoretically formulated and a provably correct solution algorithm is obtained. The most transparent specification automaton essentially shows the precedence ordering among events from a minimal cardinality set that is relevant to the intended requirement, and should help towards resolving the long-standing problem in specification, namely: how do we know that a specification in automata does indeed capture the intended control requirement?
Starting Page	1474
Ending Page	1479
File Size	374967
Page Count	6
File Format	PDF
ISBN	9781424450381
ISSN	10504729
DOI	10.1109/ROBOT.2010.5509246
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Automata Automatic control Robotics and automation Control systems Discrete event systems Manufacturing automation Intelligent robots Specification languages USA Councils Automatic logic units transparency specification automata language relevance
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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