State-based control of fuzzy discrete-event systems

Cao, Y; Ying, M; Chen, G

State-based control of fuzzy discrete-event systems

Cao, Y Ying, M

Chen, G

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2007, 37 (2), pp. 410 - 424
Issue Date:: 2007-04-01

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Field	Value	Language
dc.contributor.author	Cao, Y	en_US
dc.contributor.author	Ying, M https://orcid.org/0000-0003-4847-702X	en_US
dc.contributor.author	Chen, G	en_US
dc.date.issued	2007-04-01	en_US
dc.identifier.citation	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2007, 37 (2), pp. 410 - 424	en_US
dc.identifier.issn	1083-4419	en_US
dc.identifier.uri	http://hdl.handle.net/10453/9075
dc.description.abstract	To effectively represent possibility arising from states and dynamics of a system, fuzzy discrete-event systems (DESs) as a generalization of conventional DESs have been introduced recently. Supervisory-control theory based on event feedback has been well established for such systems. Noting that the system state description, from the viewpoint of specification, seems more convenient, we investigate the state-based control of fuzzy DESs in this paper. An approach to finding all fuzzy states that are reachable by controlling the system is presented first. After introducing the notion of controllability for fuzzy states, a necessary and sufficient condition for a set of fuzzy states to be controllable is then provided. It was also found that event- and state-based controls are not equivalent, and the relationship between them was further discussed. Finally, we examine the possibility of driving a fuzzy DES under control from a given initial state to a prescribed set of fuzzy states and then keeping it there indefinitely. © 2007 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics	en_US
dc.relation.isbasedon	10.1109/TSMCB.2006.883429	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.subject.mesh	Algorithms	en_US
dc.subject.mesh	Models, Theoretical	en_US
dc.subject.mesh	Fuzzy Logic	en_US
dc.subject.mesh	Feedback	en_US
dc.subject.mesh	Computer Simulation	en_US
dc.subject.mesh	Signal Processing, Computer-Assisted	en_US
dc.title	State-based control of fuzzy discrete-event systems	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	37	en_US
utslib.for	0803 Computer Software	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	37	en_US

Abstract:

To effectively represent possibility arising from states and dynamics of a system, fuzzy discrete-event systems (DESs) as a generalization of conventional DESs have been introduced recently. Supervisory-control theory based on event feedback has been well established for such systems. Noting that the system state description, from the viewpoint of specification, seems more convenient, we investigate the state-based control of fuzzy DESs in this paper. An approach to finding all fuzzy states that are reachable by controlling the system is presented first. After introducing the notion of controllability for fuzzy states, a necessary and sufficient condition for a set of fuzzy states to be controllable is then provided. It was also found that event- and state-based controls are not equivalent, and the relationship between them was further discussed. Finally, we examine the possibility of driving a fuzzy DES under control from a given initial state to a prescribed set of fuzzy states and then keeping it there indefinitely. © 2007 IEEE.

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http://hdl.handle.net/10453/9075