On-Line Evaluation of Systems with Discrete Observations

Abstract This paper presents a method for detecting faults in systems with discrete observations. We examine systems representable by a behavioral model. The behavioral model framework characterizes the time evolution of systems with discrete and continuous states and uncertainty in model parameters. Our method for detecting faults depends on an on-line encoding of the set of trajectories corresponding to a given observation and the dynamics specifications of the behavioral model. This encoding, called an evolution graph, is modified on-line as new observations are received. Faults are detected when the set of encoded trajectories is determined to be empty. This paper presents the modelling framework and discusses the construction and maintenance of the evolution graph.

[1]  Gul A. Agha,et al.  ACTORS - a model of concurrent computation in distributed systems , 1985, MIT Press series in artificial intelligence.

[2]  Jean Florine,et al.  Firmware transitional logic for on-line monitoring and control , 1986, 1986 25th IEEE Conference on Decision and Control.

[3]  Lawrence E. Holloway,et al.  Fault detection and diagnosis in manufacturing systems: a behavioral model approach , 1990, [1990] Proceedings. Rensselaer's Second International Conference on Computer Integrated Manufacturing.

[4]  Orna Grumberg,et al.  Research on Automatic Verification of Finite-State Concurrent Systems , 1987 .

[5]  W. M. Wonham,et al.  A framework for real-time discrete event control , 1990 .

[6]  Bruce H. Krogh,et al.  Integration of behavioral fault-detection models and an intelligent reactive scheduler , 1991, Proceedings of the 1991 IEEE International Symposium on Intelligent Control.

[7]  R. Greiner,et al.  Dynamical logic observers for finite automata , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.