Abstract
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.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call