Identification for Piezoelectric Smart Materials based on Neural Networks method

Author

Yanmei, Liu ; Zhen, Chen ; Dingyu, Xue

Author_Institution

Dept. of Autom., Shenyang Inst. of Aeronaut. Eng., Shenyang, China

Volume

2

fYear

2010

fDate

27-29 March 2010

Firstpage

608

Lastpage

611

Abstract

Based on the static Preisach hysteresis model of Piezoelectric Smart Materials, the technology of Artificial Neural Networks is applied for the hysteresis modeling of Piezoelectric Smart Materials. The BP network is chosen as the method of identifying the non-linear hysteresis sysytem. Adopting this method one sample´s hysteresis model is built. The results have shown that this method is correct and effective.

Keywords

backpropagation; composite materials; intelligent actuators; intelligent materials; magnetic hysteresis; neurocontrollers; nonlinear control systems; piezoelectric actuators; piezoelectric materials; polymers; BP network; IPMC actuator; artificial neural network; hysteresis modeling; ionic polymer-metal composite; nonlinear hysteresis sysytem; piezoelectric smart material; static Preisach hysteresis model; Artificial neural networks; Biomembranes; Electric potential; Magnetic hysteresis; Magnetic materials; Neural networks; Piezoelectric actuators; Piezoelectric materials; Polymers; Space technology; Artificial Neural Networks; Preisach hysteresis model; identifying; non-linear;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Computer Control (ICACC), 2010 2nd International Conference on

Conference_Location

Shenyang

Print_ISBN

978-1-4244-5845-5

Type

conf

DOI

10.1109/ICACC.2010.5486712

Filename

5486712