中文摘要：

针对经典Preisach模型存在的不能反映迟滞依赖于输入变化率的动态特性且其权重函数难以确定的缺点，给出了Preisaeh模型中积分项的一种实现形式，动态Preisach算子，其参数是输入变化率的函数，该Preisach算子反映了迟滞依赖输入变化率而体现的动态特性的基誉特征．通过引入动态Preisach算子，将存在于迟滞非线性中的多值映射转化为连续的一一映射，从而将神经网络等智能辨识工具应用到迟滞非线性的建模中。该方法简化了迟滞非线性的建模过程，结构简单，且能实现在线更新，具有实际的应用价值，实验结果验证了所得模型的有效性。

英文摘要：

The classic Preisach model is hard to be used to describe the dynamics of the hysteresis depending on the input change-rate. Moreover, the weighting function of the Preisach model is rather difficult to be determined so that it is impossible to adapt the change of the environmental conditions. A modified Preisach model, namely the dynamic Preisach operator, was proposed, wherein, the parameters are dependent on the change-rate of the input to describe the basic feathers of the dynamics of the hysteresis caused by the input change-rate. With the introduction of the dynamic Preisach operator into the input space, the multi-valued mapping of the hysteresis is transformed into the one-to-one mapping so the neural networks can be utilized for the identification of the rate-dependent hysteresis. The proposed model has a simple architecture that simplifies identification procedure for hysteresis and can adapt to different operating conditions. Finally, experimental results are illustrated to show the effectiveness of the proposed approach.