【摘要】 提出一种不对称指数函数迟滞算子,其形状参数为输入电压变化率的函数,因此算子的形状实时变化且不具有对称性。在此基础上构造动态Preisach模型,并利用神经网络完成其辨识。实验结果表明,该动态迟滞模型能够精确地描述压电陶瓷执行器的动态迟滞现象。在多种频率的电压信号激励下,与双S函数迟滞模型相比,该动态迟滞模型预测位移的均方误差(MSE)减小了0.20以上,最大绝对值误差减小了0.84μm以上。更多还原

【Abstract】 This paper proposed an asymmetric exponential function hysteresis operator,whose shape parameters were related to the input rate,so the shape of the new operator is variable and asymmetric.A dynamic Preisach model was built based on the new operator,and identified by the neural network.The experimental results show that the new dynamic model can describe the dynamic hysteresis of the piezoceramic actuators accurately.Under multi-frequency signals,the mean square error predicted by this new model reduces more than 0.20,and the max absolute error reduce more than 0.84μm,when compared with the double-S function hysteresis model.更多还原