• 제목/요약/키워드: roll rate sensor

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Development of Hardware-in-the-loop Simulator for Spacecraft Attitude Control using thrusters

  • Koh, Dong-Wook;Park, Sang-Young;Choi, Kyu-Hong
    • 한국우주과학회:학술대회논문집(한국우주과학회보)
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    • 한국우주과학회 2008년도 한국우주과학회보 제17권2호
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    • pp.35.3-36
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    • 2008
  • The ground-based spacecraft simulator is a useful tool to realize various space missions and satellite formation flying in the future. Also, the spacecraft simulator can be used to develop and verify new control laws required by modern spacecraft applications. In this research, therefore, Hardware-in-the-loop (HIL) simulator which can be demonstrated the experimental validation of the theoretical results is designed and developed. The main components of the HIL simulator which we focused on are the thruster system to attitude control and automatic mass-balancing for elimination of gravity torques. To control the attitude of the spacecraft simulator, 8 thrusters which using the cold gas (N2) are aligned with roll, pitch and yaw axis. Also Linear actuators are applied to the HIL simulator for automatic mass balancing system to compensate for the center of mass offset from the center of rotation. Addition to the thruster control system and Linear actuators, the HIL simulator for spacecraft attitude control includes an embedded computer (Onboard PC) for simulator system control, Host PC for simulator health monitoring, command and post analysis, wireless adapter for wireless network, rate gyro sensor to measure 3-axis attitude of the simulator, inclinometer to measure horizontality and battery sets to independently supply power only for the simulator. Finally, we present some experimental results from the application of the controller on the spacecraft simulator.

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Development of a Hardware-in-the-loop Simulator for Spacecraft Attitude Control Using Thrusters

  • Koh, Dong-Wook;Park, Sang-Young;Kim, Do-Hee;Choi, Kyu-Hong
    • Journal of Astronomy and Space Sciences
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    • 제26권1호
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    • pp.47-58
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    • 2009
  • In this study, a Hardware-In-the-Loop (HIL) simulator using thrusters is developed to validate the spacecraft attitude system. To control the attitude of the simulator, eight cold gas thrusters are aligned with roll, pitch and yaw axis. Also linear actuators are applied to the HIL simulator for automatic mass balancing to compensate the center of mass offset from the center of rotation. The HIL simulator consists of an embedded computer (Onboard PC) for simulator system control, a wireless adapter for wireless network, a rate gyro sensor to measure 3-axis attitude of the simulator, an inclinometer to measure horizontal attitude, and a battery set to supply power for the simulator independently. For the performance test of the HIL simulator, a bang-bang controller and Pulse-Width Pulse-Frequency (PWPF) modulator are evaluated successfully. The maneuver of 68 deg. in yaw axis is tested for the comparison of the both controllers. The settling time of the bang -bang controller is faster than that of the PWPF modulator by six seconds in the experiment. The required fuel of the PWPF modulator is used as much as 51% of bang-bang controller in the experiment. Overall, the HIL simulator is appropriately developed to validate the control algorithms using thrusters.

관성 센서를 이용한 휴머노이드 로봇용 3축 자세 추정 알고리듬 개발 (Development of 3-Dimensional Pose Estimation Algorithm using Inertial Sensors for Humanoid Robot)

  • 이아람;김정한
    • 제어로봇시스템학회논문지
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    • 제14권2호
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    • pp.133-140
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    • 2008
  • In this paper, a small and effective attitude estimation system for a humanoid robot was developed. Four small inertial sensors were packed and used for inertial measurements(3D accelerometer and three 1D gyroscopes.) An effective 3D pose estimation algorithm for low cost DSP using an extended Kalman filter was developed and evaluated. The 3D pose estimation algorithm has a very simple structure composed by 3 modules of a linear acceleration estimator, an external acceleration detector and an pseudo-accelerometer output estimator. The algorithm also has an effective switching structure based on probability and simple feedback loop for the extended Kalman filter. A special test equipment using linear motor for the testing of the 3D pose sensor was developed and the experimental results showed its very fast convergence to real values and effective responses. Popular DSP of TMS320F2812 was used to calculate robot's 3D attitude and translated acceleration, and the whole system were packed in a small size for humanoids robots. The output of the 3D sensors(pitch, roll, 3D linear acceleration, and 3D angular rate) can be transmitted to a humanoid robot at 200Hz frequency.

SVM 이용한 다중 생체신호기반 온열질환 감지 스마트 안전모 개발 (Smart Helmet for Vital Sign-Based Heatstroke Detection Using Support Vector Machine)

  • 장재민;이강호;주수빈;권오원;이학;이동규
    • 센서학회지
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    • 제31권6호
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    • pp.433-440
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    • 2022
  • Recently, owing to global warming, average summer temperatures are increasing and the number of hot days is increasing is increasing, which leads to an increase in heat stroke. In particular, outdoor workers directly exposed to the heat are at higher risk of heat stroke; therefore, preventing heat-related illnesses and managing safety have become important. Although various wearable devices have been developed to prevent heat stroke for outdoor workers, applying various sensors to the safety helmets that workers must wear is an excellent alternative. In this study, we developed a smart helmet that measures various vital signs of the wearer such as body temperature, heart rate, and sweat rate; external environmental signals such as temperature and humidity; and movement signals of the wearer such as roll and pitch angles. The smart helmet can acquire the various data by connecting with a smartphone application. Environmental data can check the status of heat wave advisory, and the individual vital signs can monitor the health of workers. In addition, we developed an algorithm that classifies the risk of heat-related illness as normal and abnormal by inputting a set of vital signs of the wearer using a support vector machine technique, which is a machine learning technique that allows for rapid binary classification with high reliability. Furthermore, the classified results suggest that the safety manager can supervise the prevention of heat stroke by receiving feedback from the control system.