DocumentCode :
3414403
Title :
A new modeling formalism and automata model generator for a class of discrete event systems
Author :
Chandra, V. ; Kumar, R.
Author_Institution :
Dept. of Electr. Eng., Kentucky Univ., Lexington, KY, USA
Volume :
6
fYear :
2001
fDate :
2001
Firstpage :
4562
Abstract :
The control of discrete event systems (DES) requires a correct model of the system and of its control specifications. In this paper we present a new modeling formalism for generating valid models of complex systems. The class of systems this applies to, is one which consists of signals that take binary values. The technique presented here makes task of modeling considerably less cumbersome, less error prone, and is user-friendly. Another advantage of using this modeling formalism is that the size of the system model is polynomial in the number of signals; whereas the number of states in the automata models is exponential in the number of signals. We present automated techniques for deriving a state machine based model from the model in the proposed formalism. Such a state machine model can then be used for the purpose of automated supervisor synthesis for which a vast body of tools already exists, based upon the Ramadge & Wonham (1987) supervisory control theory (SCT). We illustrate the modeling formalism using examples drawn from manufacturing systems and process control
Keywords :
automata theory; computational complexity; discrete event systems; large-scale systems; modelling; DES; SCT; automata model generator; automated supervisor synthesis; complex systems; discrete event system control; manufacturing systems; modeling formalism; process control; state machine; supervisory control theory; user-friendly technique; Automata; Automatic control; Control system synthesis; Control theory; Discrete event systems; Induction generators; Manufacturing systems; Polynomials; Process control; Signal synthesis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
ISSN :
0743-1619
Print_ISBN :
0-7803-6495-3
Type :
conf
DOI :
10.1109/ACC.2001.945698
Filename :
945698
Link To Document :
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