Abstract
Networked embedded systems are composed of a large number of components that interact with the physical world via a set of sensors and actuators, have their own computational capabilities, and communicate with each other via a wired or wireless network. Such systems are best modeled by distributed hybrid systems that capture the interaction between the physical and computational components. Monitoring and diagnosis of any dynamical system depend crucially on the ability to estimate the system state given the observations. Estimation for distributed hybrid systems is particularly challenging because it requires keeping track of multiple models and the transitions between them. This paper presents a particle filtering based estimation algorithm for a class of distributed hybrid systems. The hybrid estimation methodology is demonstrated on a cryogenic propulsion system.
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
A. Balluchi, L. Benvenuti, M. D. Benedetto, and A. Sangiovanni-Vincentelli. Design of observers for hybrid systems. In C. Tomlin and M. Greenstreet, editors, Hybrid Systems: Computation and Control (HSCC’02), Vol. 2289, LNCS, 76–89. Springer-Verlag, 2002.
M. Black and D. Fleet. Probabilistic detection and tracking of motion boundaries. International Journal of Computer Vision, 38(3):231–245, 2000.
A. Doucet, N. D. Freitas, and N. Gordon, editors. Sequential Monte Carlo Methods in Practice. Statistics for Engineering and Information Science. Springer, 2001.
M. Hofbaur and B. Williams. Mode estimation of probabilistic hybrid systems. In C. Tomlin and M. Greenstreet, editors, Hybrid Systems: Computation and Control (HSCC’02), Vol. 2289, LNCS, 253–266. Springer-Verlag, 2002.
M. Isard and A. Blake. A mixed-state condensation tracker with automatic model switching. In Proc. of the 6th International Conference on Computer Vision, pages 107–112, 1998.
W. Jackson, M. Fromherz, D. Biegelsen, J. Reich, and D. Goldberg. Constrained optimization based control of real time large scale systems: Airjet movement object system. In Proc. of the 40th IEEE Conference on Decision and Control, pages 4717–4720, Orlando, FL, December 2001.
D. Koller and U. Lerner. Sampling in factored dynamic systems. In Doucet et al. [3], pages 445–464.
X. Koutsoukos, F. Zhao, H. Haussecker, J. Reich, and P. Cheung. Fault modeling for monitoring and diagnosis of sensor-rich hybrid systems. In Proc. of the 40th IEEE Conference on Decision and Control, pages 793–801, Orlando, FL, December 2001.
X. Koutsoukos, J. Kurien, and F. Zhao. Estimation of Hybrid Systems Using Particle Filtering Methods. In Proc. of MTNS 2002, Notre Dame, IN, August 2002.
J. Kurien, X. Koutsoukos, and F. Zhao. Distributed diagnosis of networked hybrid systems. In AAAI Spring Symposium on Information Refinement and Revision for Decision Making: Modeling for Diagnostics, Prognostics, and Prediction, pages 37–44, Stanford, CA, March 2002.
S. McIlraith, G. Biswas, D. Clancy, and V. Gupta. Hybrid systems diagnosis. In N. Lynch and B. Krogh, editors, Hybrid Systems: Computation and Control, Vol. 1790, LNCS, 282–295. Springer, 2000.
A. Nerode and W. Kohn. Models for hybrid systems: Automata, topologies, controllability, observability. In R. L. Grossman, A. Nerode, A. P. Ravn, and H. Rischel, editors, Hybrid Systems, Vol. 736, LNCS, 317–356. Springer-Verlag, 1993.
F. Zhao, X. Koutsoukos, H. Haussecker, J. Reich, P. Cheung, and C. Picardi. Distributed monitoring of hybrid systems: A model-directed approach. In Proc. IJCAI’2001, pages 557–564, Seattle, WA, 2001.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Koutsoukos, X., Kurien, J., Zhao, F. (2003). Estimation of Distributed Hybrid Systems Using Particle Filtering Methods. In: Maler, O., Pnueli, A. (eds) Hybrid Systems: Computation and Control. HSCC 2003. Lecture Notes in Computer Science, vol 2623. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36580-X_23
Download citation
DOI: https://doi.org/10.1007/3-540-36580-X_23
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00913-9
Online ISBN: 978-3-540-36580-8
eBook Packages: Springer Book Archive