A Fuzzy Logic-based Expert System for generating SCADA of Caterpillar engine

The development of a fuzzy logic-based expert system module to predict the fault diagnosis of software modules under uncertainty and non-precision of data was proved in this study. The expert system's rule-base and database are tuned using a Fuzzy logic system. A supervision system enabled an intelligent decision-making system to achieve the goals of the degree of variation, failure type, and location. The use of a fuzzy logic-based expert system to generate SCADA for a caterpillar CAT 3126B has been proposed. The main object of a fuzzy knowledge-based system is implemented by simulating the caterpillar's parameters in the SIMULINK/MATLAB environment. An intelligent Scada system uses an expert system to detect events and situations, to reason with the events, and then come up with a response, such as giving advice or taking corrective actions.