摘要
在Preisach模型的结构下,用一阶微分方程代替relay迟滞元,借鉴对角动态神经网络模型,提出压电陶瓷迟滞特性的一种新的数学模型。该模型既有Preissach模型的结构思想,又能反映其动态特性。在输入信号是周期性衰减信号的激励下,由Preisach模型产生的数据和压电陶瓷产生的数据分别进行建模和预测仿真,结果表明该模型用于压电陶瓷迟滞特性建模是有效的,并具有较高的模型精度。
The dynamic neural network hysteresis model of the piezoceramic actuator is presented by using the similar diagonal current neural network. This model is of structure of the Preisach model of which hysteresis cell is replaced by first-order differential equation. Simulation and experimental results performed on the two kinds of decayed rectangular input signals show that this new approach of identification and prediction for the piezoceramic actuator is effective and can achieve high accuracy.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2005年第4期7-12,共6页
Journal of Mechanical Engineering
基金
国家自然科学基金(50265001)广西区教委科研(桂教科研[2003]22号)资助项目
关键词
PREISACH模型
一阶微分方程
压电陶瓷迟滞特性
似对角动态神经网络模型
Preisach model First-order differential equation Hysteresis behavior of the piezoceramic actuator Similar diagonal recurrent neural network
