Error Correction Method of Sensor Based on Fuzzy-KF for Measurement of Drilling Cuttings

Liang, Haibo; Chen, Haifeng; Guo, Jinhong; Xing, Zuo

doi:10.1109/jsen.2022.3157260

Cited by 1 publication

(1 citation statement)

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“…In practical applications, systems are influenced by both internal and external uncertainties, and the statistical characteristics of process noise and measurement noise can easily change, exhibiting strong time-varying properties 25 . Reference 26 proposed an adaptive fuzzy-KF model based on fuzzy criteria, which enables real-time updates of process noise and measurement noise. Additionally, the Sage-Husa adaptive filter can also estimate noise statistical characteristics in real time but cannot guarantee the positive definiteness of the noise covariance matrix and the semipositive definiteness of the process noise covariance matrix 27,28 .…”

Section: Introductionmentioning

confidence: 99%

Designing of Airspeed Measurement Method for UAV Based on MEMS Pressure Sensors

chen,

Li,

et al. 2024

Preprint

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Airspeed measurement is crucial for UAV control. To achieve accurate airspeed measurements for UAV, this paper calculates airspeed data by measuring changes in air pressure and temperature. Based on this, a data processing method based on mechanical filtering and improved AR-SHAKF algorithm is proposed to indirectly measure airspeed with high precision. In particular, a mathematical model for an airspeed measurement system is established, and an installation method for the pressure sensor is designed to measure the total pressure, static pressure and temperature. Secondly, the measurement principle of the sensor are analyzed, and a metal tube is installed to act as a mechanical filter, particularly in cases where the aircraft has a significant impact on the gas flow field. Furthermore, a time-series model is used to establish the sensor state equation and the initial noise values. It also enhances the Sage-Husa adaptive filter to analyze the unavoidable error impact of initial noise values. By constraining the range of measurement noise, it achieves adaptive noise estimation. To validate the superiority of the proposed method, a low-complexity airspeed measurement device based on MEMS pressure sensors is designed. The results demonstrate that the airspeed measurement device and the designed velocity measurement method can effectively calculate airspeed with high measurement accuracy and strong interference resistance.

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