[1] [1] RAKOTONDRABE M.Bouc-Wen modeling and inverse multiplicative structure to compensate hysteresis nonlinearity in piezoelectric actuators［J］.Automation Science and Engineering,IEEE Transactions on,2011,8(2):428-431.

[2] [2] FUNAHASHI K I.On the approximate realization of continuous mappings by neural networks［J］.Neural Networks,1989,2(3):183-192.

[3] [3] ADLY A A,ABD-EL-HAFIZ S K.Using neural networks in the identification of preisach-type hysteresis models［J］.IEEE Trans Magn,1998,34(3):629-635.

[4] [4] LI Chuntao,TAN Yonghong.A neural networks model for hysteresis nonlinearity［J］.Sensors Actuators A:Phys,2004,112(1):49-54.

[5] [5] DONG R L,TAN Y H,CHEN H,et al.A neural networks based model for rate-dependent hysteresis for piezoceramic actuators［J］.Sensors Actuators A:Phys,2008,143(2):370-376.

[6] [6] CHENG L,LIU W C,HOU Z G,et al.Neural-network-based nonlinear model predictive control for piezoelectric actuators［J］.IEEE Trans Ind Electron,2015,62(12):7717-7727.

[7] [7] WU Y N,FANG Y C,LIU C H,et al.Gated recurrent unit based frequency-dependent hysteresis modeling and end-to-end compensation［J］.Mech Syst Signal Process,2020,136:106501.