Sensor selection for observability in Interpreted Petri Nets: a genetic approach

Author

Aguirre-Salas, L.

Author_Institution

Dept. de Ingenierias, Centro Univ. de la Costa Sur., XXX, Mexico

Volume

4

fYear

2003

fDate

9-12 Dec. 2003

Firstpage

3760

Abstract

This paper addresses the minimal cost sensor selection problem for observability in Interpreted Petri Nets (IPN) models of Discrete Event Systems (DES). A simple genetic algorithm to solve this problem is presented. This procedure takes advantage of a characterization of the observability property for IPN models presented in a previous work. Such characterization is based on the event-detectability and marking-detectability properties, which can be tested in a polynomial time. The presented genetic algorithm is quite simple and helps to reduce the design effort and time of DES.

Keywords

Petri nets; discrete event systems; genetic algorithms; observability; DES; IPN models; discrete event systems; event detectability properties; genetic algorithm; interpreted Petri nets models; marking detectability properties; observability; polynomial time; sensor selection; Algorithm design and analysis; Costs; Discrete event systems; Genetic algorithms; Observability; Petri nets; Polynomials; Sensor phenomena and characterization; Sensor systems; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2003. Proceedings. 42nd IEEE Conference on

ISSN

0191-2216

Print_ISBN

0-7803-7924-1

Type

conf

DOI

10.1109/CDC.2003.1271734

Filename

1271734