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...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.展开更多
基金supported by the National Natural Science Foundation of China(No.61273184)the Program for Changjiang Scholars and Innovative Research Team in University(No.IRT13097)the Natural Science Foundation of Zhejiang Province(Nos.LY15F030022, LY13E050025,LZ15F030005)
文摘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.
