A Plant Control Expert System to Cope with Unforeseen Situations.

概要

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In order to reduce labor and careless mistakes in plant control operations, supervisory control systems using expert system technologies have been developed. These control systems can handle foreseen situations, however, due to a lack of the appropriate control rules, they cannot handle unforeseen situations. Up until now, such situations have had to be handled by skilled operators. To overcome such unforeseen situations, the authors have developed model-based reasoning technologies, such as diagnosis with qualitative causal model, knowledge compiler generating control knowledge from plant models (structure, function and general rules) and fuzzy qualitative reasoning. This paper proposes an overall system concept and architecture which integrates these technologies. This system was developed by first observing how skilled operators handle unforeseen situations, and then emulating such actions. This paper highlights the importance of predicting and monitoring the results of applying generated control rules to the plant, and re-generating new control rules in the case that the unforeseen situation could not be restored to a normal situation. The proposed architecture has been successfully applied to an experimental thermal power plant control system.
公益社団法人計測自動制御学会の論文