Abstract
The paper deals with the diagnosis of continuous-variable or hybrid systems whose state can be measured only by means of a quantiser. Hence, the on-line information used in the diagnosis is given by the sequences of input and output events. The paper describes how the quantised system can be represented by a semi-Markov process and how the diagnostic problem can be solved by using this timed discrete-event representation. A specific result is obtained if the model is does not include probabilistic information about the event occurrence. The diagnostic method is illustrated by considering a numerical example which concerns a part of a batch process. The results show that the temporal information included in the semi-Markov process is crucial for fault diagnosis of discrete-event systems.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
G. Lichtenberg, A. Steele: “An approach to fault diagnosis using parallel qualitative observers”, Workshop on Discrete Event Systems, Edinburgh 1996, pp. 290–295.
J. Lunze: A Petri-net approach to qualitative modeling of continuous dynamical systems, Systems Analysis, Modelling, Simulation, 9 (1992), pp 88–111.
J. Lunze, “Qualitative modelling of linear dynamical systems with quantized state measurements”, automatica 30 (1994), pp. 417–431.
J. Lunze, “A timed discrete-event abstraction of continuous-variable systems”, Intern. J. Control 72 (1999), pp. 1147–1164.
J. Lunze, “Diagnosis fo quantised systems based on a timed discrete-event model”, IEEE Trans. SMC-30 (2000), No. 5.
J. Lunze, B. Nixdorf, B., J. Schröder, “On the nondeterminism of discrete-event representations of continuous-variable systems,” automatica 35 (1999), 395–408.
J. Lunze, F. Schiller, “An example of fault diagnosis by means of probabilistic logic reasoning”, SAFEPROCESS, Hull 1997; extended version to appear in Control Engineering Practice 7 (1999), pp. 271–278.
J. Lunze; J. Schröder: Process diagnosis based on a discrete-event description, Automatisierungstechnik 47 (1999), 358–365.
J. Lunze; T. Serbesow: Logikbasierte Prozeßdiagnose unter Berücksichtigung der Prozeßdynamik, Messen, Steuern, Regeln 34 (1991), 163–165 und 253–257.
J. Raisch, S. O’Young, “A totally ordered set of discrete abstractions for a given hybrid or continuous system”, In: P. Antsaklis, W. Kohn, A. Nerode, S. Sastry, Eds., Hybrid Systems IV, Lecture Notes in Computer Science, vol. 1273, pp. 342–360 Berlin: Springer-Verlag, 1997.
M. Sampath, R. Sengupta, S. Lafurtune, K. Sinnamohideen, D. Teneketzis, “Diagnosability of discrete event systems”, IEEE Trans., vol. AC-40, pp. 1555–1575, 1995.
V.S. Srinivasan, M.A. Jafari, “Fault detection/monitoring using timed Petri nets”, IEEE Trans., vol. SMC-23, 1993.
O. Stursberg; S. Kowalewski; S. Engell: Generating timed discrete models, 2-nd MATHMOD, Vienna 1997, pp. 203–207.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lunze, J. (2000). Diagnosis of Quantised Systems by Means of Timed Discrete-Event Representations. In: Lynch, N., Krogh, B.H. (eds) Hybrid Systems: Computation and Control. HSCC 2000. Lecture Notes in Computer Science, vol 1790. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46430-1_23
Download citation
DOI: https://doi.org/10.1007/3-540-46430-1_23
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67259-3
Online ISBN: 978-3-540-46430-3
eBook Packages: Springer Book Archive