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Design of a neuro-fuzzy controller for speed control applied to AC servo motor

In this study, a neuro-fuzzy controller which has the characteristic of fuzzy control and an artificial neural network is designed. A fuzzy rule to be applied is automatically selected by the allocated neurons. The neurons correspond to fuzzy rules that are created by an expert. To adapt the more precise modeling, error backpropagation learning of adjusting the link-weight of fuzzy membership function in the Neuro-Fuzzy controller is implemented. The more classified fuzzy rule is used to include the property of the dual mode method. In order to verify the effectiveness of the algorithm designed above, an operating characteristic of an AC servomotor with variable load is investigated.