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Dynamic systems reliability evaluation using uncertainty techniques for performance monitoring

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2 Author(s)
O. Wolkenhauer ; Control Syst. Centre, Univ. of Manchester Inst. of Sci. & Technol., UK ; J. Edmunds

The authors suggest the use of fuzzy measures and fuzzy integrals in evaluating the reliability of control systems by approximating an expert's view on a complex system when assessing the performance. The class of systems considered have structural complexity exhibiting a closed form model of the underlying process. The approach may be described in three parts where in the first stage a rule based classifier (`spy') extracts `states of performance' from the process. It is shown that the rule premise resembles a possibility based control chart and that the possibilistic version, embedded in a rule based system offers a comprehensive man process interface while having a similar or slightly improved speed of detection. The reliability can be quantified based on a finite set of abstract states over which a certainty measure is defined. A prediction for a specified reliability interval of time is done by using a qualitative model akin to Markov stochastic processes and consequently decisions are made to alter the system structure. This framework allows distinct classes of uncertainty to be considered

Published in:

IEE Proceedings - Control Theory and Applications  (Volume:144 ,  Issue: 1 )