FOURIER SERIES-BASED AUTOMATIC GENERATION SYSTEM AND METHOD FOR MULTI-VARIABLE FUZZY SYSTEMS

A method of automatically generating a multi-variable fuzzy inference system using a Fourier series expansion. Sample sets are decomposed into a cluster of sample sets associated with given input variables. Fuzzy rules and membership functions are computed individually for each variable by solving a single input multiple outputs fuzzy system extracted from the set cluster. The resulting fuzzy rules and membership functions are composed and integrated back into the fuzzy system appropriate for the original sample set with a minimal computational cost. In addition, an overall system error can be related to errors at each stage of decomposition and composition, enabling error bounds or accuracy thresholds for each stage to be specified and ensuring the final precision of the resulting fuzzy system on the original sample set.