Extraction of fuzzy knowledge base from measurement dat

In recent years, the applications of Fuzzy Logic have been gaining recognition due to their ability to deal with information represented in linguistic form. A Fuzzy logic expert system consists of a Knowledge Base with rule sets which can be used to define systems that are difficult to represent mathematically.;This paper presents an efficient method of extracting a fuzzy knowledge base from Numerical data. Two separate models have been used to extract the knowledge base for two different systems. The first extracted knowledge base can be used to estimate the State of Charge (SOC) of a 9V, 160 mAh Nickel Metal Hydride battery while the second extracted knowledge base can be used to estimate the force required to balance an inverted pendulum. The first problem involves collecting data by means of a Controlled Discharge Method using Arduino Board while for the second problem the Inverted Pendulum is to be modelled in Simulink and then the data is to be collected by running the simulation numerous times.;The data collected is systemized and handled by means of coding in Microsoft Visual Studio C++. The two case studies represented in this paper represents a very efficient method of extracting a Knowledge Base from a numerical data provided that the collected data is concrete. This can be applied to any complex systems and once the extraction is done the Knowledge Base can be used to calculate the output for a given input.