• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.563-566
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• 1991

This paper discusses the possibility of applying fuzzy logic controller in a microprocessor - based servomotor controller, such as servomotor position controller, which requires faster and more accurate response compared with other industrial processes. According to the fuzzy control rule made by tie analysis of error and error change, one Look-up table that contains various quantized step is made and appropriate initial error change is selected to the good responses.

• 한국항행학회논문지
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• 제28권4호
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• pp.379-385
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• 2024

관성항법장치는 정지 상태에서 가속도계 및 자이로 센서가 측정한 중력과 지구 자전 각속도 정보를 이용하여 정렬을 수행하며, 일반적으로 선형 항법 오차 모델 기반의 영속도 보정 칼만필터를 사용하여 수행된다. 하지만 이는 정지 상태를 가정하여 설계된 알고리즘으로 해상 정박 중 정렬을 수행하는 경우, 파도로 인해 발생하는 움직임으로 정렬 오차가 커지거나 필터가 발산하게 된다. 본 논문에서는 큰 방위각 오차 모델과 초기위치 보정 기법을 사용하여 해상 플랫폼을 위한 정박 중 정렬 알고리즘을 설계하고 시뮬레이션을 통해 검증하였다. 또한 이를 회전형 관성항법장치에 적용하였을 경우 바이어스가 상쇄되는 원리를 통해 비약적으로 성능이 개선됨을 확인하였다.

• 한국항공우주학회지
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• 제47권4호
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• pp.283-288
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• 2019

본 논문은 천리안위성 2A호가 2018년도 12월 5일에 발사되고 태양전지판구동기의 초기운영을 수행하면서 획득된 텔레메트리를 통해 지상에서 개발하고 시험한 결과에 대한 우주검증 결과를 정리하였다. 특히, 전이궤도 이후 정지궤도에 진입하면서 태양전지판구동기의 위치 설정 로직과 open-loop 제어에 의한 누적오차 보상 로직에 대한 결과를 검증하고 정상 운영이 되고 있음을 확인할 수 있었다. 또한, 설계 단계에서 확인되지 못했던 정지궤도 대비 태양의 위치가 시간에 따라 주기적인 오프셋이 있음을 발견하고 그에 적합한 보정 threshold 값을 설정하게 된 결과도 정리하였다.

• Journal of Astronomy and Space Sciences
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• 제34권2호
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• pp.127-138
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• 2017

The current study designs the mission orbit of the lunar CubeSat spacecraft to measure the lunar local magnetic anomaly. To perform this mission, the CubeSat will impact the lunar surface over the Reiner Gamma swirl on the Moon. Orbit analyses are conducted comprising ${\Delta}V$ and error propagation analysis for the CubeSat mission orbit. First, three possible orbit scenarios are presented in terms of the CubeSat's impacting trajectories. For each scenario, it is important to achieve mission objectives with a minimum ${\Delta}V$ since the CubeSat is limited in size and cost. Therefore, the ${\Delta}V$ needed for the CubeSat to maneuver from the initial orbit toward the impacting trajectory is analyzed for each orbit scenario. In addition, error propagation analysis is performed for each scenario to evaluate how initial errors, such as position error, velocity error, and maneuver error, that occur when the CubeSat is separated from the lunar orbiter, eventually affect the final impact position. As a result, the current study adopts a CubeSat release from the circular orbit at 100 km altitude and an impact slope of $15^{\circ}$, among the possible impacting scenarios. For this scenario, the required ${\Delta}V$ is calculated as the result of the ${\Delta}V$ analysis. It can be used to practically make an estimate of this specific mission's fuel budget. In addition, the current study suggests error constraints for ${\Delta}V$ for the mission.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.534-540
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• 1993

In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algrithms need a special perfect position sensor or a priori information about error sources, while ours does not. To our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterative learning algorithm does not have the drawbacks of the existing iterative learning control theories. To be more specific, our algorithm learns a uncertain function inself rather than its special time-trajectory and does not request the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.

• 전자공학회논문지B
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• 제31B권9호
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• pp.57-66
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• 1994

In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algorithms need a special perfect position sensor or a priori information about error sources, while ours does not. to our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterativelearning algorithm does not have the drawbacks of the existing interativelearning control theories. To be more specivic, our algorithm learns an uncertain function itself rather than its special time-trajectory and does not reuquest the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.

• 동력기계공학회지
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• 제21권6호
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• pp.101-109
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• 2017

The pneumatic driving system has advantages such as high output power per weight and low heat generation rate. However, it is difficult to control the position because of its strong non-linearity such as large friction forces compared to driving force, and heat transfer characteristics that change during operation. Therefore, in order to achieve the control objectives, a robust controller should be designed considering modeling error and model uncertainty. In this paper, a sliding mode controller is designed to improve the position control performance of pneumatic cylinder driving system. Experimental results show that the designed controller achieves the designed control objectives even if the model of the cylinder driving system, such as the initial pressure inside the cylinder and the initial position of the piston is changed.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1996년도 봄 학술발표회 논문집
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• pp.1-8
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• 1996

Many studies showed that small imperfections can also have a considerable influence on the behaviour of structures. Especially, in Single-Layer Latticed Domes, initial imperfection occurred by human error and construction error is very important to the buckling load. The definition of imperfection is that a node of structure shifts from perfect condition. For example, in the case of truss structures, imperfections are represented by shifting the location of nodal points relative to the position in which they would be for a perfect structure. This paper uses Arc-length Method in nonlinear iteration analysis, choosing star dome, in which many studies have been accomplished, as a model. The results of analysis show that initial imperfection can reduce the buckling load of structures.

• 한국군사과학기술학회지
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• 제19권4호
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• pp.435-442
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• 2016

For inertial navigation systems, initial information such as position, velocity and attitude is required for navigation. Self-alignment is the process to determine initial attitude on stationary condition using inertial measurements such as accelerations and angular rates. The accuracy of self-alignment is determined by inertial sensor error. As soon as an inertial navigation system is powered on, the temperature of accelerometer rises rapidly until temperature stabilization. It causes acceleration error which is called temperature stabilizing error of accelerometer. Therefore, temperature stabilizing error degrades the alignment accuracy and also increases alignment time. This paper suggests a method to calculate azimuthal attitude using curve fitting of horizontal control angular rate in fixed-gain self-alignment. It is verified by simulation and experiment that the accuracy is improved and the alignment time is reduced using the proposed method under existence of the temperature stabilizing error.

• 전기학회논문지
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• 제60권10호
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• pp.1915-1923
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• 2011

For automated guidance control of a magnetically guided-all wheel steered vehicle, it is necessary to have information about position and orientation of the vehicle, and deviations from the reference path in real time. The magnet reference system considered here consists of three magnetic sensors mounted on the vehicle and magnetic markers, which are non-equidistantly buried in the road. This paper presents an observer to estimate such position and orientation at the center of gravity of the vehicle. This algorithm is based on the simple kinematic model of vehicle and uses the data of wheel velocity, steering angle, and the discrete measurements of marker positions. Since this algorithm requires the exact values of initial states, we have also proposed an algorithm of determining the initial position and orientation from the 16 successive magnet pole data, which are given by the magnetic measurement system(MMS). The proposed algorithm is capable of continuing to estimate for the case that the magnetic sensor fail to measure up to three successive magnets. It is shown through experimental data that the proposed algorithm works well within permissible error range.