The present invention relates to a magnetic hysteresis modeling based on the new matching of a piezoelectric actuator using an adaptive neurofuzzy inference system (ANFIS), and a compensator therefor, and proposes a new approach for modeling and compensation for the distortion factor-independent magnetic hysteresis of the piezoelectric actuator. A model named magnetic hysteresis based on matching was developed on the basis of two very important features of magnetic hysteresis, which are matching and wipe-out. The proposed approach consists of two parts for a monotonous increase and decrease of input excitation. In order to recognize the model, a data set of primary minor loop values will be determined in advance. To this end, an ANFIS technique and experimental data are able to be used. By using the technique, the input-output relationship of the primary minor loop values was efficiently evaluated. In addition, the ANFIS technique is used to construct a data set of reverse primary minor loop values, which is essential for a magnetic hysteresis compensator based on matching. Several experiments in modeling and open loop control are conducted to exhibit the efficiency of the proposed approach. Additionally, a comparative study between the proposed approach and one previous study is undertaken to express the availability of the proposed approach. According to the present invention, a piezoelectric actuator is able to show very high performance with high precision.
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