Magnetoresistive angle position sensors are, beside Hall effect sensors, especially suitable for usage within servo systems due to their reliability, longevity, and resilience to unfavorable environmental conditions. The proposed distributed method for self-calibration of magnetoresistive angular position sensor uses the data collected during the highest allowed speed shaft movement for the identification of the measurement process model parameters. Data acquisition and initial data processing have been realized as a part of the control process of the servo system, whereas the identification of the model parameters is a service of an application server. The method of minimizing of the sum of algebraic distances of the sensor readings and the parametrized model is employed for the identification of parameters of linear compensation, whereas the average shaft rotation speed has been used as a high precision reference for the identification of parameters of harmonic compensation. The proposed method, in addition to a fast convergence, provides for the increase in measurement accuracy for an order of magnitude. Experimentally obtained measurement uncertainty was better than 0.5°, with the residual variance less than 0.02°, comparable to the sensor resolution.

中文翻译：

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伺服系统内磁阻角位置传感器的分布式自校准方法

除了霍尔效应传感器之外，磁阻角度位置传感器由于其可靠性、使用寿命和对不利环境条件的适应能力而特别适合在伺服系统中使用。所提出的用于磁阻角位置传感器自校准的分布式方法使用在最高允许速度轴运动期间收集的数据来识别测量过程模型参数。数据采集​​和初始数据处理已作为伺服系统控制过程的一部分实现，而模型参数的识别则是应用服务器的一项服务。采用最小化传感器读数代数距离之和的方法和参数化模型来识别线性补偿的参数，而平均轴转速已被用作谐波补偿参数识别的高精度参考。所提出的方法，除了快速收敛之外，还提供了一个数量级的测量精度增加。实验获得的测量不确定度优于0.5°，剩余方差小于0.02°，与传感器分辨率相当。