• 대한조선학회논문집
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• 제61권2호
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• pp.98-105
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• 2024

Due to the low accuracy of measured data obtained from low-cost GNSS and IMU devices, it was hard to secure the required accuracy of the measured position and heading angle for autonomous navigation which was conducted by a model-scale marine mobility. In this paper, a localization technique using the Extended Kalman Filter (EKF) is proposed for coping with the issue. First of all, a position and heading angle estimator is developed using EKF with the assumption of a point mass model. Second, the measured data from GNSS and IMU, including position, heading angle, and velocity are used for the estimator. In addition, the heading angle is additionally obtained by comparing the LiDAR point cloud with map information for a temporal water tank. The newly acquired heading angle is integrated into the estimator as an additional measurement to correct the inaccuracy in the heading angle measured from the IMU. The effectiveness of the proposed approach is investigated using data acquired from preliminary tests of the model-scale autonomous marine mobility.

• 전기학회논문지
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• 제67권10호
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• pp.1308-1316
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• 2018

Accurate tuning of parameter is very important in vector-controlled induction motor. Among the parameters of induction motor, detuning of rotor resistance used in controller design deteriorates drive performance. This paper presents a novel rotor resistance estimation strategy using slip angular velocity in vector-controlled induction motor drives. The slip angular velocity can be calculated by two methods. Firstly, it can be induced from the rotor voltage equation. Secondly, it can be induced from the difference between synchronous angular velocity and rotor angular velocity. The first method includes the rotor resistance, while the second method dose not include this parameter. From this fact, the rotor resistance can be identified by comparing the slip angular velocities in the two methods. In the tuned states of the rotor resistance, performances of flux estimator and speed drive are discussed. The simulation and experimental results are given to verify the validity of the proposed method in various situations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1116-1121
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• 1991

In this paper the feedback linearization of the valve-controlled nonlinear hydraulic velocity control system and the Implementation of the digital state feedback controller is studied. The C.inf. nonlinear transformation to the electro-hydraulic velocity control system, which transforms nonlinear system to linear equivalent one, is obtained. It is shown that this transformation Is global one. The digital controller to this linearized model is obtained by using the one-step ahead state estimator and implemented to real plant. The proposed method In this paper is easier to implement than other proposed methods and it is possible to control in real tine. The experiment and simulation study show that the implementation of the digital state feedback controller based on the feedback linearized model is successful.

• Multiscale and Multiphysics Mechanics
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• 제1권3호
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• pp.261-270
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• 2016

The longitudinal velocity (forward speed) having significant importance in proper running of railway wheelset on track, depends greatly upon the adhesion ratio and creep analysis by implementation of suitable dynamic system on contamination. The wet track condition causes slip and slide of vehicle on railway tracking, whereas high speed may also increase slip and skidding to severe wear and deterioration of mechanical parts. The basic aim of this research is to design appropriate model aimed estimator that can be used to control railway vehicle forward velocity to avoid slip. For the filtration of disturbance procured during running of vehicle, the kalman filter is applied to estimate the actual signal on preferered samples of creep co-efficient for observing the applied attitude of noise. Thus error level is detected on higher and lower co-efficient of creep to analyze adhesion to avoid slip and sliding. The skidding is usually occurred due to higher forward speed owing to procured disturbance. This paper guides to minimize the noise and error based upon creep coefficient.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1822-1825
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• 2003

A practical range estimator based on the robust Kalman filter is proposed to solve the range estimation problem for surface to air missile(SAM) homing guidance. Apart from the previous works based on the extended Kalman filter(EKF) with bearing only measurement, the proposed scheme makes use of line-of-sight(LOS) rate to ensure the fast convergency at long-range. In this reason, the robust Kalman filter is considered to deal with LOS rate measurement error. The recursive linear structure of proposed filter is easy to implement and make it possible to reduce computational burdens. Moreover, it shows good estimation performance without specific guidance law such as oscillation proportional navigation guidance(OPNG).

• 대한기계학회논문집A
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• 제30권8호
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• pp.880-888
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• 2006

This paper presents the sliding mode control with the perturbation estimator for a nonlinear control system in the presence of perturbations including external disturbances, unpredictable parameter variations, ana unstructured dynamics. The proposed perturbation estimator is based on the Recursive Linear Smoothed Newton predictive algorithm so that it is effective to attenuate an undesired noise in high frequency band and to predict the present perturbation signal from the previous ones. Compared to conventional sliding mode control (SMC) and sliding mode control with perturbation estimation (SMCPE) introduced by Elmali and Olgac, the control algorithm proposed in this study can offer better tracking control performances and more feasible estimation characteristics. The effectiveness and superiority of the proposed control strategy are demonstrated by a series of simulations on the position tracking control of a simple two-link robot manipulator subject to velocity feedback signals including white noises.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2076-2078
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• 2002

This paper presents an Intelligent Balance Beam Controller(IBBC) which can estimate the inertia of load automatically. Balance Beam controller is a kind of construction tool which can control the attitude of the load hanging in the air such as a beam carried by crane. In our previous work, Balance Beam had been built to control the object in air using a mechanical gyro system having a position controllable gimbal structure. In field application the load inertia for operation is not easy to figure out because the weight and shape which determines the inertia, varies depending on the object to be carried. Therefore it is difficult for a worker to operate a Balance Beam and an accident could be caused occasionally. We designed an automatic load estimator to measure the inertia of arbitrary load by using an angular velocity sensor that is installed on the Balance Beam. Simulation results and current status for implementation are presented.

• 대한기계학회논문집
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• 제18권1호
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• pp.166-174
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• 1994

A critical evaluation is made of the spectral bias which occurs in the use of a laser doppler velocimeter(LDV). Two processing algorithms are considered for spectral estimates: the sample and hold interpolation method(SH) and the nonuniform Shannon reconstruction technique(SR). Assessment is made of these for varying data densities $(0.05{\le}d.d.{\le}5)$ and turbulence levels(t.i.=30%, 100%). As an improved version of the spectral estimator, the utility of POCS (the projection onto convex sets) has been tested in the present study. This algorithm is found useful to be in the region when $d.d.{\gep}3.$

• 대한의용생체공학회:의공학회지
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• 제37권1호
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• pp.21-30
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• 2016

Weibull distribution with two parameters, shape (k) and scale (s) parameters are used to model the fatigue failure analysis due to periodic vortex shedding of the synovial fluid in knee joints. In order to determine the later parameter, a suitable statistical model is required for velocity distribution of synovial fluid flow. Hence, wide applicability of Weibull distribution in life testing and reliability analysis can be applied to describe the probability distribution of synovial fluid flow velocity. In this work, comparisons of three most widely used methods for estimating Weibull parameters are carried out; i.e. the least square estimation method (LSEM), maximum likelihood estimator (MLE) and the method of moment (MOM), to study fatigue failure of bone joint due to periodic vortex shedding of synovial fluid. The performances of these methods are compared through the analysis of computer generated synovial fluidflow velocity distribution in the physiological range. Significant values for the (k) and (s) parameters are obtained by comparing these methods. The criterions such as root mean square error (RMSE), coefficient of determination ($R^2$), maximum error between the cumulative distribution functions (CDFs) or Kolmogorov-Smirnov (K-S) and the chi square tests are used for the comparison of the suitability of these methods. The results show that maximum likelihood method performs well for most of the cases studied and hence recommended.

• 한국정보통신학회논문지
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• 제26권1호
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• pp.104-113
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• 2022

본 논문에서는 OFDM 레이다를 위한 딥러닝 기반 표적의 거리 및 속도 추정 기법을 제안한다. 제안하는 기법은 표적으로부터 반사된 수신 신호를 받아 변조신호 제거 후 2차원 FFT를 통해 2차원 주기도를 얻는다. 주기도는 기존 및 제안 방법에서 표적의 거리 및 속도를 추정하는 입력신호이다. 주기도에서 정점은 표적의 위치를 나타내는데 표적의 거리 및 속도 추정을 위해 널리 사용되는 기존 기법은 CFAR (Constant False Alarm Rate) 알고리즘이다. 반면 제안하는 기법은 다중 출력 CNN (Convolutional Neural Network)을 이용하여 거리 및 속도를 추정한다. 기존 기법과 달리 제안 기법은 주기도 이외에 잡음 전력과 같이 추가적인 정보가 필요하지 않아 사용하기 편리하다. 컴퓨터 시뮬레이션 결과에 따르면 제안 추정 기법은 기존 기법보다 거리 및 속도 추정 MSE (Mean Square Error)오차 성능을 5배 이상 개선하며 송신 OFDM 심볼 개수가 증가할수록 정확도가 향상되는 특성을 보인다.