RULE-BASED FUZZY-LOGIC CONTROLLER FOR A PWR-TYPE NUCLEAR-POWER-PLANT

In this study, a rule-based fuzzy logic regulator was developed for a PWR-type nuclear power plant based on knowledge acquisition through numerical simulations and making use of a validated mathematical model of the H. B. Robinson power plant. Production rules were used for knowledge representation and fuzzy sets were implemented using broken lines. Due to the nature of the rules, forward chaining was selected as the inferencing mechanism. Using an error criterion, the gain and sampling interval values were adjusted. The behavior of this rule-based controller was investigated under both normal and noisy operating conditions and in the presence of drift in process variables. It was observed that there was negligible degradation in the performance of the controller in the presence of noise and drift in process variables.