TY - GEN
T1 - Improvement of the accuracy of absolute magnetic encoders based on automatic calibration and the fuzzy phase-locked-loop
AU - Tran, Thuong Ngoc Cong
AU - Nguyen, Ha Xuan
AU - Park, Jae Wan
AU - Jeon, Jae Wook
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/15
Y1 - 2017/12/15
N2 - This paper presents an approach for the improvement of the accuracy of absolute magnetic encoders (AME). The encoders comprise the following two magnets: a multipolar magnet to increase the resolution and the accuracy, and a center-located bipolar magnet for the calculation of the absolute angle. The multipolar signal processing is crucial for the increasing of the encoder accuracy; however, the multipolar signals are not ideal, i.e, dc offsets, different amplitudes, phase shifts, and random noise. The present paper proposes a calibration method that is based on the adaptive linear neural network (ADALINE) for the reduction of the effect of the nonidealities. In addition, to optimize the loop-acquisition time and to enhance the random-noise reduction, the bandwidth is adapted using the fuzzy phase-locked-loop (F-PLL). This method is simulated using Matlab software and is implemented on the ARM STM32F405R. The study results demonstrate the efficient high performance that can be achieved with the use of the proposed method.
AB - This paper presents an approach for the improvement of the accuracy of absolute magnetic encoders (AME). The encoders comprise the following two magnets: a multipolar magnet to increase the resolution and the accuracy, and a center-located bipolar magnet for the calculation of the absolute angle. The multipolar signal processing is crucial for the increasing of the encoder accuracy; however, the multipolar signals are not ideal, i.e, dc offsets, different amplitudes, phase shifts, and random noise. The present paper proposes a calibration method that is based on the adaptive linear neural network (ADALINE) for the reduction of the effect of the nonidealities. In addition, to optimize the loop-acquisition time and to enhance the random-noise reduction, the bandwidth is adapted using the fuzzy phase-locked-loop (F-PLL). This method is simulated using Matlab software and is implemented on the ARM STM32F405R. The study results demonstrate the efficient high performance that can be achieved with the use of the proposed method.
KW - Absolute magnetic encoder
KW - fuzzy phase-locked-loop
KW - magnetic encoder calibration
KW - sinusoidal encoders
UR - https://www.scopus.com/pages/publications/85046699579
U2 - 10.1109/IECON.2017.8216560
DO - 10.1109/IECON.2017.8216560
M3 - Conference contribution
AN - SCOPUS:85046699579
T3 - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
SP - 3310
EP - 3315
BT - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
Y2 - 29 October 2017 through 1 November 2017
ER -