Model-based Prognostics of Hybrid Systems

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Matthew Daigle Indranil Roychoudhury Anibal Bregon

Abstract

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) pre- diction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

How to Cite

Daigle, M. ., Roychoudhury, . I. ., & Bregon, . A. . (2015). Model-based Prognostics of Hybrid Systems. Annual Conference of the PHM Society, 7(1). https://doi.org/10.36001/phmconf.2015.v7i1.2586
Abstract 21 | PDF Downloads 5

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Keywords

prediction, prognosis, Hybrid Systems, NAS

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Section
Technical Papers

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