STUDY ON SIMILAR DIAGNAL DYNAMIC NEURAL NETWORK
HYSTERESIS MODEL FOR PIEZOCERAMIC ACTUATOR
BASED ON PREISACH MODEL

Dang Xuanju

(Institute of Automation, Shanghai  Jiaotong University, Shanghai 200030)

Tan Yonghong

(Laboratory of Intelligent System and Control Engineering, Guilin Institute of Electronic Technology, Guilin 541004)

Abstract: 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.

Key words: Preisach model  First-order differential equation  Hysteresis behavior of the piezoceramic actuator  Similar diagonal recurrent neural network

CLC No: TH703.8

国家自然科学基金(50265001)和广西区教委科研(桂教科研[2003]22号)资助项目. Received 20040618, received in revised form 20041112