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2 International Journal of Applied Mathematics and Computer Science

2 1999

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Neural Network Evaluation of Model-Based Residuals in Fault Detection of Time Delay Systems

Zitek P., Mankova R., Hlava J.

International Journal of Applied Mathematics and Computer Science

1999

Vol. 9, no 3

599-617

Model-based fault detection becomes rather questionable if a supervised plant belongs to the class of systems with distributed parameters and significant delays. Two methods of fault detection have been developed for this class of plants, namely a method of functional (anisochronic) state observer and a modified internal model control scheme adopted for that purpose. Both these model schemes are employed to generate residuals, i.e. differences suitable to watch whether a malfunction of the control operation has occurred. Continuous evaluation of residuals is provided by means of a dynamic application of artificial neural networks (ANNs). This evaluation is carried out on the basis of prediction of time series evolution, where the accordance obtained between the prediction and measured outputs is used as a classification criterion. Implementation of both the methods is demonstrated on a laboratory-scale heat transfer set-up, making use of the Real-Time Matlab software.

Evolutionary Multi-Objective Pareto Optimisation of Diagnostic State Observers

Kowalczuk Z., Suchomski P., Białaszewski T.

International Journal of Applied Mathematics and Computer Science

1999

Vol. 9, no 3

689-709

A multi-objective Pareto-optimisation procedure for the design of residual generators which constitute a primary instrument for model-based fault detection and isolation (FDI) in systems of plant monitoring and control is considered. An evolutionary approach to the underlying multi-objective optimisation problem is utilised. The resulting robust observer detector allows for FDI, taking into account the issue of false alarms.