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A New Model Based on Adaptation of the External Loop to Compensate the Hysteresis of Tactile Sensors

机译:基于外环自适应补偿触觉传感器滞后的新模型

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This paper presents a novel method to compensate for hysteresis nonlinearities observed in the response of a tactile sensor. The External Loop Adaptation Method (ELAM) performs a piecewise linear mapping of the experimentally measured external curves of the hysteresis loop to obtain all possible internal cycles. The optimal division of the input interval where the curve is approximated is provided by the error minimization algorithm. This process is carried out off line and provides parameters to compute the split point in real time. A different linear transformation is then performed at the left and right of this point and a more precise fitting is achieved. The models obtained with the ELAM method are compared with those obtained from three other approaches. The results show that the ELAM method achieves a more accurate fitting. Moreover, the involved mathematical operations are simpler and therefore easier to implement in devices such as Field Programmable Gate Array (FPGAs) for real time applications. Furthermore, the method needs to identify fewer parameters and requires no previous selection process of operators or functions. Finally, the method can be applied to other sensors or actuators with complex hysteresis loop shapes.
机译:本文提出了一种新颖的方法来补偿在触觉传感器的响应中观察到的滞后非线性。外部环路自适应方法(ELAM)对磁滞环路的实验测量外部曲线进行分段线性映射,以获得所有可能的内部周期。误差最小化算法提供了近似曲线的输入间隔的最佳划分。该过程是离线进行的,并提供参数以实时计算分裂点。然后,在此点的左侧和右侧执行不同的线性变换,从而获得更精确的拟合。将使用ELAM方法获得的模型与通过其他三种方法获得的模型进行比较。结果表明,ELAM方法可以实现更精确的拟合。此外,所涉及的数学运算更简单,因此更容易在诸如用于实时应用的现场可编程门阵列(FPGA)的设备中实现。此外,该方法需要识别较少的参数,并且不需要操作员或功能的先前选择过程。最后,该方法可以应用于具有复杂磁滞回线形状的其他传感器或执行器。

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