Model-based Prognostics of Hybrid Systems

Matthew Daigle, Indranil Roychoudhury, and Anibal Bregon
Submission Type: 
Full Paper
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phmc_15_012.pdf406.16 KBAugust 18, 2015 - 9:57am

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) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

Publication Year: 
2015
Publication Volume: 
6
Publication Control Number: 
012
Submission Keywords: 
prognosis
Hybrid Systems
prediction
NAS
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
Modeling and simulation
Systems and platform applications
Submitted by: 
  
 
 
 

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