• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.65-66
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• 2007

본 논문은 파라미터 변동에 잘 적응하며 강인한 영구자석 동기전동기의 위치센서 없는 센서리스 제어를 위해 개선된 슬라이딩 모드 관측기에 고정자 저항 추정기능을 추가한 새로운 슬라이딩 모드 적응 관측기를 제안한다. 제안된 관측기는 개선된 슬라이딩 모드 관측기를 사용함으로써 기존의 슬라이딩 모드 관측기에서 채터링(Chattering) 문제 해결을 위해 저역통과필터(Low-pass filter)의 사용 및 추가적인 회전자의 위치보상은 Sigmoid 함수를 스위칭 함수로 사용하므로 제거 할 수가 있다. 또한 고정자 저항 추정기능을 추가하여 센서리스 운행 중 환경적 요인으로 인한 고정자 저항값의 변동이나 초기에 고정자 저항값을 잘못 알고 있더라도 빠른 적응을 통해서 추정오차를 절감시켜 전동기의 속도추정 성능을 향상시킬수 있다. 또한 기존의 적응 슬라이딩 모드 관측기에서의 적분연산을 줄임으로써 제어시스템의 성능을 개선시켰다 제안된 관측기의 안정성은 Lyapunov 후보 함수를 이용하여 관측기의 이득을 설정함으로써 검증하였으며 관측기의 성능은 시뮬레이션을 통한 실험을 통하여 그 타당성을 입증하였다.

• Geophysics and Geophysical Exploration
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• v.1 no.1
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• pp.49-56
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• 1998

Seismic tomography has been widely used as high resolution subsurface imaging techniques in engineering applications. Although most of the techniques have been using travel time inversion, waveform method is being driven forward owing to the progress of computational environments. Although full-waveform inversion method has been known as the best method in terms of model resolving power without high-frequency restriction and weak scattering approximation, it has practical disadvantage that it is apt to get stuck in local minimum if the initial guess is far from the actual model and it consumes so much time to calculate. In this study, 2-D full-waveform inversion algorithm in acoustic medium is developed, which uses result of traveltime tomography as initial model. From the application on synthetic data, it is proved that this approach can efficiently reduce the problem of conventional approaches: our algorithm shows much faster convergence rate and improvement of model resolution. Result of application on physical modeling data also shows much improvement. It is expected that this algorithm can be applicable to real data.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.10
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• pp.64-76
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• 1998

In this paper, we propose the dynamic modeling, path planning and tracking algorithms of 4-wheeled 2-d.o.f.(degree of freedom) mobile robot(WMR). The gaussian functions are applied to design the smooth path of WMR. To calculate the WMR position in real time, we use three components of inertial measurement units(IMU). These units have initial error because of the rotation rate of earth, gravity acceleration and so on. Therefore we derive the initial error model of IMU, and compare the fitness diagnosis about probability characteristics of real data adn estimated data. The performance of IMU with error model and Kalman filter is compared to that without filter and error model. The simulation results show that the proposed dynamic model, path planning and tracking algorithms are more useful than the conventional control algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2172-2177
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• 2015

The DF-MZEP-CME (decision feedback - maximum zero-error probability for constant modulus errors) algorithm that makes the probability for constant modulus error (CME) close to zero and employs decision feedback (DF) structures shows more improved performance in channel distortion compensation. However the DF-MZEP-CME algorithm has a computational complexity proportional to a sample size for probability estimation and this property plays a role of an obstacle in practical implementation. In this paper, the gradient of DF-MZEP-CME is proposed to be estimated recursively and shown to solve the computational problem by making the algorithm independent of the sample size. For a sample size N, the conventional method has 10N multiplications but the proposed has only 20 regardless of N. Also the recursive gradient estimation for weight update is kept in continuity from the initial state to the steady state without any error propagation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.51-60
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• 2002

The Monte-Carlo simulation of statistical analysis is used to investigate the final conditions of states as well as the footprint boundaries resulting from the atmospheric re-entry dispersions. The re-entry dispersions in this paper are specified by a $7\times7$ covariance matrix of latitude, longitude, altitude, bank angle, flight path angle, heading error, and range at entry velocity. The error sources that affect these at re-entry for a deboost are the uncertainties associated with atmospheric density and temperature, initial errors, wind, and estimation error of aerodynamic coefficients. Using $3{\sigma}_n$ deviations of these errors and a nominal flight trajectory, the covariance matrix of state variables can be determined by performing a trajectory error analysis. Major considerations in the application of the Monte-Carlo method are the simulation of perturbed trajectories, bank reversal, and determination of the impact points for each of these trajectories. This paper analyzes the results of uncertainties from the viewpoint of aero-coefficients and bank reversal.

• Journal of Ocean Engineering and Technology
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• v.19 no.6 s.67
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• pp.78-85
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• 2005

Initial alignment and localization are important topics in inertial navigation systems, since misalignment and initial position error wholly propagate into the navigation systems and deteriorate the performance of the systems. This paper presents the error convergence characteristics of the hybrid navigation system for underwater vehicles initial position, which is based on an inertial measurement unit (IMU) accompanying a range sensor. This paper demonstrates the improvement on the navigational performance oj the hybrid system with the range information, especially focused on the convergence of the estimation of underwater vehicles initial position error. Simulations are performed with experimental data obtained from a rotating ann test with a fish model. The convergence speed and condition of the initial error removal for random initial position errors are examined with Monte Carlo simulation. In addition, numerical simulation is conducted with an AUV model in lawn-mowing survey mode to illustrate the error convergence of the hybrid navigation System for initial position error.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1125-1139
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• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.

• Convergence Security Journal
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• v.13 no.5
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• pp.97-105
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• 2013

It is very important the government project should be supported by enough budget for proceeding. The insufficient budget by poor budget estimating uesd to bring about discontinuing for the project. This is originally caused by inaccuracy for cost estimating about system and evaluating for system requirements on the projet initial phase. The system requirements is technical requirements that converted the user needs and is needs for communicating between stakeholder and developer and manufacturer. Also the system requirements is the primary factor to make the project cost. The cost estimating is not easy due to complication of cost factors and an aberration between cost estimating and actual cost. Specially, on the project initial phase, shortage of detail information for project make more difficult to do cost estimating. This study proposes the architecture for validating proper system requirements by using cost estimations methodology on the project initial phase and shows the computer tool for simulating the proposed architecture.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.2
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• pp.164-172
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• 2008

This paper presents the efficient localization of a mobile robot traveling on the floor with tags installed, using the spatial and temporal information acquired from passive RFID environment. Compared to previous research, the proposed localization method can reduce the position estimation error and also cut down the initial cost tag installation cost. Basically, it is assumed that a mobile robot is traveling over a series of straight line segments, each at a certain constant velocity, and that the number of tags sensed by a mobile robot at each sampling instant is at most one. First, the velocity and position estimation of a mobile robot starting from a known position, which is valid for all segments except the first one. Second, for the first segment in which the starting position is unknown, the velocity and position estimation is made possible by enforcing a mobile robot to traverse at least two tags at a constant velocity with the steering angle unchanged. Third, through experiments using our passive RFID localization system, the validity and performance of the mobile robot localization proposed in this paper is demonstrated.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.5
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• pp.376-385
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• 2017

In this paper, a method for the estimation of structural displacements using structure's mode shapes and accelerations is suggested to reduce the disadvantages of acceleration time integration method. Acceleration time integration method requires accurate information on initial conditions, and errors caused by noise can be accumulated during time integration. To avoid these problems, the method for the estimation of structural displacements based on mode superposition method is developed and two vibration experiments for cantilever beam are conducted to verify this method. Static displacements and dynamic displacements of beam structure are estimated using measured accelerations from experiments and mode shapes of cantilever beam, and they are compared with measured displacements using laser displacement sensor. From these results, the validity and usefulness of this method are verified.