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• W2117353755 abstract "The velocity and acceleration estimations by first-order and second-order differentiation of the position data from optical incremental encoder for servo motors have serious errors. Single-dimensional Kalman filter (SDKF) is proposed to estimate velocity with less complexity. Based on velocity and its variation, a polynomial expression multiplied by exponential is established to compute in real time the adaptive noise variance approximately, which can be applied to the Kalman filter. Regarding SDKF-filtered velocity as reference input, phase-locked loop (PLL) structure is employed to estimate acceleration, which adopts integral operation instead of differentiation. The simulation and experimental results demonstrate that the estimated velocity and acceleration by the proposed methods have more precision and less noise than that by differentiation method. Streszczenie. Analizowano bląd określania szybkości i przyśpieszenia na podstawie danych o pozycji otrzymanych z optycznego enkodera. Zaproponowano wykorzystanie filtru Kalmana do określania predkości. Do określania przyśpieszenia wykorzystano uklad PLL. Uzyskano poprawe dokladnocci i zmniejszenie szumow. (Wyznaczanie szybkości i przyśpieszenia z wykorzystaniem filtru Kalman z adaptacyjną wariancją szumow)" @default.
• W2117353755 created "2016-06-24" @default.
• W2117353755 creator A5032198553 @default.
• W2117353755 creator A5067290849 @default.
• W2117353755 date "2012-01-01" @default.
• W2117353755 modified "2023-09-23" @default.
• W2117353755 title "Velocity and acceleration computations by single-dimensional Kalman filter with adaptive noise variance" @default.
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