• Title/Summary/Keyword: MEMS-based inertial sensor

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Performance analysis of feedback controller for vibratory gyroscope at various vacuum levels

  • Sung, Woon-Tahk;Lee, Jang-Gyu;Kang, Tae-Sam
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1537-1541
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    • 2003
  • In this paper, presented is a feedback control performance of vibratory gyroscope at various vacuum levels. Micro gyroscope, whose operation is based on the vibrating motion at the vacuum conditions, is highly influenced by the vacuum level of the operating circumstances. In general, we apply the feedback control scheme to the gyroscope in order to improve the performances of the sensor. And control performances of the gyroscope are related to those vacuum levels. So we need investigate the performances of the closed loop control at various vacuum conditions comparing with those of the open loop. The experimental results show that the sensitivity of the closed loop is less than that of the open loop especially in low vacuum conditions. Therefore, there should be trade-off between sensitivity and other sensor performances such as linearity, bandwidth when we apply feedback control to the gyroscope.

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Performance Improvement of an AHRS for Motion Capture (모션 캡쳐를 위한 AHRS의 성능 향상)

  • Kim, Min-Kyoung;Kim, Tae Yeon;Lyou, Joon
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.12
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    • pp.1167-1172
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    • 2015
  • This paper describes the implementation of wearable AHRS for an electromagnetic motion capture system that can trace and analyze human motion on the principal nine axes of inertial sensors. The module provides a three-dimensional (3D) attitude and heading angles combining MEMS gyroscopes, accelerometers, and magnetometers based on the extended Kalman filter, and transmits the motion data to the 3D simulation via Wi-Fi to realize the unrestrained movement in open spaces. In particular, the accelerometer in AHRS is supposed to measure only the acceleration of gravity, but when a sensor moves with an external linear acceleration, the estimated linear acceleration could compensate the accelerometer data in order to improve the precision of measuring gravity direction. In addition, when an AHRS is attached in an arbitrary position of the human body, the compensation of the axis of rotation could improve the accuracy of the motion capture system.

Development and Application of Three-axis Motion Rate Table for Efficient Calibration of Accelerometer and Gyroscope (효율적인 각/가속도 센서 오차 보상을 위한 3 축 각도 측정 장치의 개발 및 활용)

  • Kwak, Hwan-Joo;Hwang, Jung-Moon;Kim, Jung-Han;Park, Gwi-Tae
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.7
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    • pp.632-637
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    • 2012
  • This paper introduces a simple and efficient calibration method for three-axis accelerometers and three-axis gyroscopes using three-axis motion rate table. Usually, the performance of low cost MEMS-based inertial sensors is affected by scale and bias errors significantly. The calibration of these errors is a bothersome problem, but the previous calibration methods cannot propose simple and efficient method to calibrate the errors of three-axis inertial sensors. This paper introduces a new simple and efficient method for the calibration of accelerometer and gyroscope. By using a three-axis motion rate table, this method can calibrate the accelerometer and gyroscope simultaneously and simply. Experimental results confirm the performance of the proposed method.

Development of Rotational Motion Estimation System for a UUV/USV based on TMS320F28335 microprocessor

  • Tran, Ngoc-Huy;Choi, Hyeung-Sik;Kim, Joon-Young;Lee, Min-Ho
    • International Journal of Ocean System Engineering
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    • v.2 no.4
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    • pp.223-232
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    • 2012
  • For the accurate estimation of the position and orientation of a UUV (unmanned underwater vehicle), a low-cost AHRS (attitude heading reference system) was developed using a low-cost IMU (inertial measurement unit) sensor which provides information on the 3D acceleration, 3D turning rate and 3D earth-magnetic field data in the object coordinate system. The main hardware system is composed of an IMU sensor (ADIS16405) and TMS320F28335, which is coded with an extended kalman filter algorithm with a 50-Hz sampling frequency. Through an experimental gimbal device, good estimation performance for the pitch, roll, and yaw angles of the developed AHRS was verified by comparing to those of a commercial AHRS called the MTi system. The experimental results are here presented and analyzed.