English Conference paper (Chapter in Book) Scientific

Published: IEEE [ed.]. 2004 43rd IEEE Conference on Decision and Control (CDC): Proceedings of
the 43rd IEEE Conference. (2004) ISBN:0780386825 pp. 1799-1802

Identifiers

- MTMT: 2836285
- DOI: 10.1109/CDC.2004.1430307
- IEEE Xplore: 1430307
- Scopus: 14344263856

Physics based models are often converted to monolithic systems of uncertain nonlinear
differential/algebraic equations. Graph decomposition methods can be used to decompose
such system into subsystems evolving on different time scales. This time scale separation
can be exploited to increase computational efficiency when propagating input uncertainty
in a subsystem-by-subsystem manner. In this paper, the propagation of uncertain inputs
through series, parallel and feedback interconnections of dynamical systems with simple
asymptotic behavior is studied by employing discrete density mapping (analogous to
the input-output Perron-Frobenius operator). A simple example is used to illustrate
the method.

2022-05-19 13:05