微位移系统中压电陶瓷驱动器迟滞建模

针对超精密微位移系统中压电陶瓷驱动器的迟滞非线性问题,提出了一种基于遗传反向传播(BP)神经网络的压电陶瓷迟滞非线性建模方法.通过电涡流位移传感器获取压电陶瓷驱动器不同电压值下所对应的位移值;利用六次多项式拟合获得迟滞的数学模型,从而建立基于遗传BP神经网络的迟滞,模型.实验结果显示:该迟滞模型在神经网络测试下的最大误差为0.082 1 μm,平均绝对误差为0.0158 μm.表明,所建的迟滞模型能够较精确地反映出压电陶瓷驱动器的迟滞特性,同时为微位移控制系统设计提供了一定的理论基础.

Hysteresis modeling of piezoelectric ceramic actuator in micro displacement system

Aiming at problem of hysteresis nonlinearity of piezoelectric ceramic actuator in ultra precise micro displacement system,a nonlinear hysteresis modeling method based on genetic back propagation (BP)neural network is proposed.Get the piezoelectric actuator corresponding displacement values under different voltage values by current eddy displacement sensor;secondly,mathematical model of hysteresis is obtained using six polynomial fitting,so as to establish hysteresis model based on genetic BP neural network.Experimental results show that the maximum error of the hysteresis model is and the average absolute error is.It shows that the hysteresis model can reflect the hysteresis characteristics of piezoelectric actuator accurately,and provides a theoretical basis for the design of micro displacement control system.