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Towards Diagnosing Hybrid Systems

Sheila A. McIlraith, Gautam Biswas Dan Clancy, Vineet Gupta

Year
1999
Citations
13

Abstract

This paper reports on the findings of an on-going project to investigate techniques to diagnose complex dynamic systems that are modeled as hybrid systems. In particular, we examine continuous systems with embedded supervisory controllers which experience abrupt, partial or full failure of component devices. The problem we address is: given a hybrid model of system behavior, a history of executed controller actions, and a history of observations, including an observation of behavior that is aberrant relative to the model of expected behavior, determine what fault occurred to have caused the aberrant behavior. Determining a diagnosis can be cast as a search problem. Unfortunately, the search space is extremely large. To reduce search space size and to identify an initial set of candidate diagnoses, we propose to extend techniques originally applied to qualitative diagnosis of continuous systems. We refine these diagnoses using parameter estimation and data fitting techniques. As a motiv...

Keywords

Medical diagnosisComputer scienceHybrid systemComponent (thermodynamics)ExploitFault (geology)Artificial intelligenceSet (abstract data type)Controller (irrigation)Machine learning

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