A method for selfcalibration of a magneto-resistive angular position sensor in servo systems

Abstract

Magneto-resistive and Hall angular position sensors are frequently used in servo systems, due to their reliability, longevity, and tolerance to environmental conditions. In this paper, a measurement error compensation is integrated into the servo system control structure. The compensation consists of two steps: a linear compensation of the magnetic field vector measurement error, and harmonic compensation of the angular position measurement error. The selfcalibration method uses data collected during rotation with maximal speed to identify parameters of the measurement process model. Identification is executed periodically, each time when the shaft makes a full rotation. The least squares method is utilized for identification of the linear compensation parameters, while the average rotational speed is used as an internal reference for the harmonic compensation parameters identification. The method, together with a fast convergence, increases the measurement accuracy by an order of magnitude. Experimentally achieved measurement error is below 0.7°, with residual variance below 0.05°, comparable with sensor differentiability.

A Distributed Method for Self-Calibration of Magnetoresistive Angular Position Sensor within a Servo System

“…Such a result clearly confirmed the validity of the introduction of independent compensation of the magnetic field vector measurement. Figure 9 presents the deviation of the magnetic angle from the reference angle in the third configuration experiment, without the calibration (blue), after the calibration using the method from [15] (red) and after the calibration using the proposed method (black). The largest error occurred when the distance between the magnet and the sensor was the largest, when the intensity of the magnetic field was at the sensor sensitivity boundary.…”

“…As a comparison, when the experiment was repeated in an identical manner, except that the sensor was approximately not inclined, the result was significantly different only in the direction of the offset inclination, as shown in Figure 10. Three additional calibration methods were selected for comparison, the offset compensation method based on [12], the linear compensation method based on models from [9] and [11], and the method from [15]. The methods from [10] and [13] were not considered, as they require a specific sensor, while the method from [14] requires magnetic barriers.…”

“…One of the methods for the compensation of the MR angular position sensor, applicable in the case when EOL calibration cannot be undertaken, was presented in [15]. The compensation of the measurement error consists of the linear compensation of the magnetic field vector measurement error and the harmonic compensation of the angular position measurement error.…”

“…However, a disadvantage of (self-)calibration is that a change of compensation parameters causes a momentary change of the measured position, possibly leading to an oscillatory transient process of the servo system. This was overcome in [15] by invoking the procedure for the calculation of the parameters, and their change, only when the system is in its referent position, which is calibration invariant. However, such a method would not be applicable in a distributed scenario.…”

(Retracted) Role of video sensors in observing visual image design in the construction of smart cities

“…In the coordinate distribution in the image, the first preset the exposure of a coordinate point (x,y) in the image at time t I(x,y,t) so u(x,y) and v(x,y) can be regarded as points (x,y) when the motion decomposition vectors in the x and y axis directions are decomposed, respectively. In a very short time differential dt, the point (x,y) is shifted to the pixel coordinate (x+dx,y+dy) and dx=udt,dy=vdt, which represents the relationship between the spatial gray scale of the image and the optical flow velocity 9 , 10 Table 1. is a list of parameters taken under different video sensors under the matching method.…”