Hybrid Modeling of Dynamic Physical Systems: An application in diagnosis


Model-based monitoring and diagnosis of dynamic physical systems requires well-contrained models of the system in an attempt to avoid computational intractability. The key to modeling for diagnosis is the ability to generate models that accurately describe both steady state characteristics and the dynamics of system behavior. The bond graph modeling formalism provides a suitable framework that integrates and facilitates (1) generation of behavioral constraints from physical laws, (2) expression of system dynamics in terms of energy transfer between constituent elements, and (3) modeling of steady state behavior as a special case of dynamic behavior. In dynamic physical systems in general, and for the purposes of diagnosis in particular, changes in the system may require a number of model switches over time. Model switches take place at discrete points in time, and combined with the typically continuous characteristic of physical systems, this naturally implies the need for hybrid models. The discrete characteristics of the behavior are modeled as finite state automata (FSA). The challenge in developing and analyzing behavior with hybrid models is to integrate the FSA and bond graph models. The end result of a set of discontinuous state changes governed by the FSA always terminates in a valid continuous state that can be analyzed using bond graph models. This research develops a comprehensive hybrid modeling theory based on physical principles which establishes (1) a formal hybrid modeling approach, (2) an analysis method for model verification, and (3) a physically correct behavior generation algorithm. An application of hybrid models to diagnosis of complex dynamic systems is also being developed.

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JANOS SZTIPANOVITS Professor of Electrical and Computer Engineering
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GAUTAM BISWAS Associate Professor of Computer Science
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GEORGE E. COOK Professor of Electrical and Computer Engineering
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