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

Area of Science:

• * Electrical Engineering
• * Sensor Technology
• * Control Systems

Background:

• * Magnetoresistive angle position sensors offer superior reliability and environmental resilience compared to Hall effect sensors for servo systems.
• * Accurate angular position sensing is critical for precise control in servo applications.
• * Existing calibration methods may lack efficiency or accuracy in dynamic conditions.

Purpose of the Study:

• * To propose and validate a distributed self-calibration method for magnetoresistive angular position sensors.
• * To enhance the measurement accuracy and convergence speed of these sensors within servo systems.
• * To leverage high-speed shaft movement data for robust parameter identification.

Main Methods:

• * A distributed approach for self-calibration using data from maximum allowed speed shaft movements.
• * Employing minimization of algebraic distances for linear compensation parameter identification.
• * Utilizing average shaft rotation speed as a high-precision reference for harmonic compensation parameter identification.
• * Integrating data acquisition and processing within the servo system's control loop, with parameter identification on an application server.

Main Results:

• * Achieved an order of magnitude increase in measurement accuracy.
• * Demonstrated fast convergence of the calibration method.
• * Experimentally obtained measurement uncertainty below 0.5°.
• * Recorded residual variance less than 0.02°, comparable to sensor resolution.

Conclusions:

• * The proposed self-calibration method significantly improves the accuracy of magnetoresistive angle position sensors.
• * The distributed approach is efficient and suitable for integration into servo system control processes.
• * The method provides high-precision angular measurements even under dynamic operating conditions.