Abstract
This paper presents an intelligent systematic methodology for enhancing diagnosability of discrete event systems by adding sensors. The methodology consists of the following iteractive steps. First, Petri nets are used to model the target system. Then, an algorithm of polynomial complexity is adopted to analyze a sufficient condition of diagnosability of the modeled system. Here, diagnosability is defined in the context of the discrete event systems theory, which was first introduced by Sampath [3]. If the system is found to be possibly non-diagnosable, T-components of the Petri net model are computed to find a location in the system for adding a sensor. The objective is to distinguish multiple T-components with the same observable event sequences. The diagnosability-checking algorithm is used again to see if the system with the newly added sensor is diagnosable. The process is repeated until either the system is diagnosable or diagnosability of the system cannot be enhanced.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Jiang, S., Kumar, R., Garcia, H.E.: Optimal Sensor Selection for discrete-Event Systems with Partial Observation. IEEE Trans. on Automatic Control 48(3), 369–381
Jiang, S., Huang, Z., Chandra, V., Kumar, R.: A Polynomial Algorithm for Testing Diagnosability of Discrete-Event Systems. IEEE Trans. on Automatic Control 46(8), 1318–1321
Sampath, M., Lafortune, S., Sinnamohideen, K., Teneketzis, D.: Diagnosability of Discrete-Event Systems. IEEE Trans. on Automatic Control 40(9), 1555–1557
Wen, Y.L., Jeng, M.D., Huang, Y.S.: Diagnosability of Semiconductor Manufacturing Equipment. Material Science Forum 505, 1135–1140
Peterson, J.L.: Petri Net Theory and the Modeling of Systems. Prentice-Hall, Englewood Cliffs (1981)
Hall, D.L., Llinas, J.: An introduction to multisensor data fusion. Proceedings of the IEEE 85(1), 6–23
Desel, J., Esparza, J.: Free Choice Petri Nets. Cambridge University Press, Cambridge (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wen, Y., Jeng, M., Jeng, L., Pei-Shu, F. (2006). An Intelligent Technique Based on Petri Nets for Diagnosability Enhancement of Discrete Event Systems. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_112
Download citation
DOI: https://doi.org/10.1007/11893004_112
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46537-9
Online ISBN: 978-3-540-46539-3
eBook Packages: Computer ScienceComputer Science (R0)