Abstract
This paper gives a survey on methods for the detection and localization of sensor and component faults of uncertain dynamic systems. In contrast to the commonly used techniques of hardware redundancy these methods make use of analytical redundancy and, thereby, allow to detect and localize faults with the aid of a digital computer. They comprise single, multiple or hierarchical state estimation using Luenberger observers or Kalman filters. An issue of particular relevance is the consideration of parameter uncertainties or parameter variations of the process. Several proposals are discussed to reduce the effects of parameter variations. Moreover, results from computer simulations and a practical technical application to the control of an inverted pendulum are reported.
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Frank, P.M. (1987). Fault Diagnosis in Dynamic Systems via State Estimation - a Survey. In: Tzafestas, S., Singh, M., Schmidt, G. (eds) System Fault Diagnostics, Reliability and Related Knowledge-Based Approaches. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3929-5_2
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DOI: https://doi.org/10.1007/978-94-009-3929-5_2
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