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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.
Natural Computation (ICNC), 2010 Sixth International Conference on (Volume:3 )
Date of Conference: 10-12 Aug. 2010