YU Cao-feng, WANG Chuan-li, WEI Ben-zhu etc. DRNN feedforward-PD feedback control for precision positioning stage based on giant magnetostrictive actuator[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 417-424
YU Cao-feng, WANG Chuan-li, WEI Ben-zhu etc. DRNN feedforward-PD feedback control for precision positioning stage based on giant magnetostrictive actuator[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 417-424 DOI: 10.3788/OPE.20152313.0417.
DRNN feedforward-PD feedback control for precision positioning stage based on giant magnetostrictive actuator
The Jiles-Atherton hysteresis model and the Dynamic Recurrent Neural Network(DRNN) feedforward-PD feedback control strategy were adopted to improve the positioning accuracy of precision positioning stage based on a Giant Magnetostrictive Actuator(GMA). An accurate hysteresis nonlinearity model of the precision positioning stage was established with the Jiles-Atherton model. A dynamics inverse model of the precision positioning stage was established with the DRNN learning method to compensate the hysteresis nonlinearity characteristic. The closed-loop PD feedback control was used to compensate the mapping error and to suppress the disturbance of DRNN. Using these control methods
the positioning accuracy of the precision positioning stage was improved. The research results show that the Jiles-Atherton hysteresis model can describe the hysteresis nonlinear characteristic of the precision positioning stage
and that DRNN feedforward-PD feedback control strategy can eliminate the nonlinear characteristics of the system
which has practical significance for improving positioning accuracy of the precision positioning stage based on the GMA.
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references
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