Towards Diagnosing Hybrid Systems.

Sheila McIlraith, Gautam Biswas, Daniel Clancy, Vineet Gupta.


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 motivating case study, we have examined the problem of diagnosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12 thrusters that enable both linear and rotational motion.

   author=    "Sheila McIlraith and Gautam Biswas and Daniel Clancy and Vineet Gupta", 
   title=     "Towards Diagnosing Hybrid Systems", 
   booktitle= "Proceedings of the 10th International Workshop on Principles of Diagnosis", 
   month=     "May", 
   year=      1999 

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