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- W2053694040 abstract "A new method for precise machining non-cylinder pin hole of piston by using embedded giant magnetostrictive smart component is presented. The intrinsic hysteresis observed in giant magnetostrictive material (GMM) has impaired the motion accuracy. A new kind of architecture of neural network is proposed to approximate the smart components hysteresis. The inverse hysteresis model of GMM smart component is achieved by CMAC network on-line learning. A real-time hysteresis compensation control strategy combining a CMAC neural network feed forward controller and a proportional derivative (PD) feedback controller is proposed to implement the precision position tracking control of the smart component. Simulation results show that this control strategy can on-line obtain inverse hysteresis model of the smart component, eliminate the hysteretic nonlinear impact and achieve the precision control of the smart component." @default.
- W2053694040 created "2016-06-24" @default.
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- W2053694040 date "2010-08-01" @default.
- W2053694040 modified "2023-09-26" @default.
- W2053694040 title "Precision position tracking control for giant magnetostrictive smart component based on CMAC self-learning" @default.
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- W2053694040 doi "https://doi.org/10.1109/icnc.2010.5582959" @default.
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