Chebyshev polynomial-based higher-order derivatives estimation from an encoder

The quantization noise in the encoder, which is a position sensor, is one factor that deteriorates the estimation performance of higher-order derivatives of position, such as velocity and acceleration. This paper aims to develop a method with smaller estimation errors than conventional methods. This paper proposes a Chebyshev polynomial-based estimation method for general higher-order derivatives. The proposed method enables better rejection of quantization noise from the measured data than using the frequency-domain method. The performance of the proposed method is validated by velocity and acceleration estimation simulations.

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Publication Details

Journal
IFAC-PapersOnLine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.ifacol.2025.10.174
Primary Topic
Sensor Technology and Measurement Systems
Type
article
Field-Weighted Citation Impact
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article

Chebyshev polynomial-based higher-order derivatives estimation from an encoder

Wataru Ohnishi, Yusuke Nomura, Takafumi Koseki, Shuji Takada et al.
IFAC-PapersOnLine
Sensor Technology and Measurement Systems
article

Chebyshev polynomial-based higher-order derivatives estimation from an encoder

Wataru Ohnishi, Yusuke Nomura, Takafumi Koseki, Shuji Takada, Adiyasuren Altanbileg, Kosuke Numata
article en

Abstract

The quantization noise in the encoder, which is a position sensor, is one factor that deteriorates the estimation performance of higher-order derivatives of position, such as velocity and acceleration. This paper aims to develop a method with smaller estimation errors than conventional methods. This paper proposes a Chebyshev polynomial-based estimation method for general higher-order derivatives. The proposed method enables better rejection of quantization noise from the measured data than using the frequency-domain method. The performance of the proposed method is validated by velocity and acceleration estimation simulations.

IFAC-PapersOnLineVol. 59(17)
Kuraray (Japan) (JP), Kitasato University (JP), The University of Tokyo (JP)
Openalex Percentile: Top 62%
Sensor Technology and Measurement Systems
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