Hysteresis Compensation of 3D Printed Sensors by a Power Law Model with Reduced Parameters

D. Kosmas, Martijn Schouten, G. Krijnen
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引用次数: 8

Abstract

We propose a modified Power Law Model [1] for hysteresis compensation. A simplification of the original model, resulting in a lower number of parameters to be estimated, is introduced. It has no nonlinear resistor in the output stage and the nonlinear resistance function in the input section(s) is given by a sinh function resulting in $3 N +2$ parameters for a model with N input stages. A cantilever beam with two symmetric piezoresistive sensors was 3D printed and shown to exhibit hysteretic behavior. The sensor’s differential measurements have been used to obtain training and validation data. We present promising fitting results obtained with a single cell model and 5 parameters only. Finally, the inverse model (compensator) is derived and applied to the experimental data in order to strongly reduce the hysteretic nonlinearity.
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基于降参数幂律模型的3D打印传感器滞回补偿
我们提出了一种修正的幂律模型[1]用于迟滞补偿。引入了对原始模型的简化,从而减少了需要估计的参数数量。它在输出级没有非线性电阻,输入段的非线性电阻函数由sinh函数给出,对于有N个输入级的模型,产生$ 3n +2$参数。一个悬臂梁与两个对称压阻传感器3D打印,并显示出滞回行为。该传感器的差分测量已用于获得训练和验证数据。我们提出了有希望的拟合结果,获得了一个单细胞模型和5个参数。最后,推导了逆模型(补偿器),并将其应用于实验数据,以有效地减小滞后非线性。
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