Towards Diagnosing Hybrid Systems

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Citation: Sheila A. McIlraith and Gautam Biswas and Dan Clancy and Vineet Gupta. (1999) Towards Diagnosing Hybrid Systems. In Knowledge Systems, AI Laboratory, February,1999.

Publication inproceedings ( Edit )
type InProceedings
bibtype inproceedings
Bibtex basics
author Sheila A. McIlraith and Gautam Biswas and Dan Clancy and Vineet Gupta
title Towards Diagnosing Hybrid Systems
booktitle Knowledge Systems, AI Laboratory
year 1999
month February
Bibtex more
note Working Notes of the AAAI 1999 Spring Symposium on Hybrid Systems and AI, 1999.
Access Paper
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. Asa motivating case study, we have examined the problem of diagnosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12thrusters that enable both linear and rotational motion.

KSL Technical Report ID: KSL-99-01
Facts about Towards Diagnosing Hybrid SystemsRDF feed
Abstract This paper reports on the findings of an o 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. Asa motivating case study, we have examined the problem of diagnosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12thrusters that enable both linear and rotational motion. enable both linear and rotational motion.
Author Sheila A. McIlraith and Gautam Biswas and Dan Clancy and Vineet Gupta  +
Bibtype inproceedings  +
Booktitle Knowledge Systems, AI Laboratory  +
Has author Sheila A. McIlraith and Gautam Biswas and Dan Clancy and Vineet Gupta  +
Has identifier KSL-99-01  +
Has publishing details February,1999  +
Has title Towards Diagnosing Hybrid Systems  +
Has where published Knowledge Systems, AI Laboratory  +
Has year 1999  +
Ksl tr id KSL-99-01  +
Month February  +
Note Working Notes of the AAAI 1999 Spring Symposium on Hybrid Systems and AI, 1999.
Process note NO  +
Title Towards Diagnosing Hybrid Systems  +
Year 1999  +
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