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A dynamic hysteresis model based on neural networks is proposed for piezoelectric actuator.Neural network has been widely applied to pattern recognition and system identification.However,it is unable to directly model the systems with multi-valued mapping such as hysteresis.In order to handle this problem,a novel hysteretic operator is proposed to extract the dynamic property of the hysteresis.Moreover,it can construct an expanded input space to transform the multi-valued mapping of hysteresis into one-to-one mapping.Then neural networks can directly be used to approximate the behavior of dynamic hysteresis.Finally,the experimental results are presented to illustrate the potential of the proposed modeling method.
A dynamic hysteresis model based on neural networks is proposed for piezoelectric actuator. Neural network has been applied widely to pattern recognition and system identification. However, it is unable to directly model the systems with multi-valued mapping such as hysteresis. this problem, a novel hysteretic operator is proposed to extract the dynamic property of the hysteresis. Moreover, it can construct an expanded input space to transform the multi-valued mapping of hysteresis into one-to-one mapping. used to approximate the behavior of dynamic hysteresis. Finaally, the experimental results are presented to illustrate the potential of the proposed modeling method.