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- A neuro-fuzzy controller has some problems that he difficulty of tuning up the membership function and fuzzy rules, long time of inferencing and defuzzifying compare to PID. Also, the fuzzy controller's own defect as a PD controller has. In this study, it is proposed two methods to sove these problems. The first method is that inner fuzzy rules are tuned up automatically by the back propagation learning according to error patterns. And the second method is a new type defuzzification method that shorten the calculation time of an inferencing and a defuzzifying. In this study, it is designed the new type neuro-fuzzy controller that improves the fast response and the stability of a system by using the proposed methods. And, the designed controller is named EPLNFC(Error pattern Learning Neuro-Fuzzy Controller). To evaluate the fast response and the stability of EPLNFC designed in this study, EPLNFC is applied to a speed control of a DC motor and AC motor.