27 May 2016 Hysteresis compensation of the piezoelectric ceramic actuators–based tip/tilt mirror with a neural network method in adaptive optics
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Abstract
The intrinsic hysteresis nonlinearity of the piezo-actuators can severely degrade the positioning accuracy of a tip-tilt mirror (TTM) in an adaptive optics system. This paper focuses on compensating this hysteresis nonlinearity by feed-forward linearization with an inverse hysteresis model. This inverse hysteresis model is based on the classical Presiach model, and the neural network (NN) is used to describe the hysteresis loop. In order to apply it in the real-time adaptive correction, an analytical nonlinear function derived from the NN is introduced to compute the inverse hysteresis model output instead of the time-consuming NN simulation process. Experimental results show that the proposed method effectively linearized the TTM behavior with the static hysteresis nonlinearity of TTM reducing from 15.6% to 1.4%. In addition, the tip-tilt tracking experiments using the integrator with and without hysteresis compensation are conducted. The wavefront tip-tilt aberration rejection ability of the TTM control system is significantly improved with the −3  dB error rejection bandwidth increasing from 46 to 62 Hz.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Chongchong Wang, Yukun Wang, Lifa Hu, Shaoxin Wang, Zhaoliang Cao, QuanQuan Mu, Dayu Li, Chengliang Yang, Li Xuan, "Hysteresis compensation of the piezoelectric ceramic actuators–based tip/tilt mirror with a neural network method in adaptive optics," Optical Engineering 55(5), 054107 (27 May 2016). https://doi.org/10.1117/1.OE.55.5.054107 . Submission:
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