An efficient tuning method for designing a fuzzy inference model

A novel fast tuning algorithm is proposed to expedite the converging process in the parameter identification of fuzzy models. In order to improve the disadvantages of the time-consuming gradient descent method, the principle of this new algorithm is only to tune the consequent parts of the fuzzy rules. The membership functions of the fuzzy model remain unchanged. The proposed tuning method is applicable to two different types of fuzzy rules. Some simulation results are given to verify that the proposed method can converge speedily and have better inference capability than conventional methods.