• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.772-778
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• 2012

In this paper, the states and the parameters in the dynamic system are simultaneously estimated by applying the UKF(Unscented Kalman Filter), which is widely used for estimating the state of non-linear systems. Estimating the parameter is very important in various fields, such as system control, modeling, analysis of performance, and prediction. Most of the dynamic systems which are dealt with in engineering have non-linearity as well as some noise. Therefore, the parameter estimation is difficult. This paper estimates the states and the parameters applying to the UKF, which is a non-linear filter and has strong noise. The augmented equation is used by including the addition of the parameter factors to the original state equation of the system. Moreover, it is simulated by applying to a 2-DOF(Degree of Freedom) dynamic system composed of the pendulum and the slide. The measurement noise of the dynamic equation is assumed to be a Gaussian distribution. As the simulation results show, the proposed parameter estimation performs better than the LSM(Least Square Method). Furthermore, the estimation errors and convergence time are within three percent and 0.1 second, respectively. Consequentially, the UKF is able to estimate the system states and the parameters for the system, despite having measurement data with noise.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.7-13
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• 2022

This paper presents a yaw moment control based on estimated mass for manual-shift commercial vehicles. In yaw moment controller, parameter uncertantiy of vehicle mass is important because the desired yaw moment depends on vehicle parameter. However, in the case of commercial vehicle, the weight of the loaded vehicle is more than twice as much as compared to the unloaded vehicle. The proposed algorithm estimates the vehicle mass by using the longitudinal dynamic and gear shifting characteristics. The estimated mass is used to adaptively modify the vehicle parameters. In addition, this paper estimates the chamber pressure of a pneumatic brake and generates the target yaw moment through on/off valve control. MATLAB/Simulink and Trucksim were performed under sine with dwell test. The results demonstrate that the proposed algorithm improves the lateral and rollover stability.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.2
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• pp.10-16
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• 2012

Currently, the majority of systems which are non-linear are in need of the correct system equations for controlling and monitoring. Therefore, the correct estimation of parameters is crucial. Generally, parameters are changed due to system deterioration or sudden environmental alterations. Given the limitations of system monitoring unstable controls can arise. In the following paper, the parameter estimation method is proposed using software filters to combat these system instabilities. For dynamic instances, a powerful particle filter is used to control the nonlinear and noisy environments in which they take place. Using a setup simulation comprised of a slider and pendulum, the state variable of noise is obtained. After collecting the data, the proposed algorithm is used to estimate both the state variable and its parameters. Finally, these results are checked with correct parameter estimations to evaluate and verify the algorithms performance.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1652_1653
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• 2009

본 논문에서는 passivity based controller에 high gain observer를 접목시킨 유압 모터의 위치 제어기를 제시 한다. 본 논문에서는 5차 비선형 동역학 모델을 사용 하였다. Passivity based controller는 유압 모터의 높은 위치 추정능력을 구현하지만 그것을 위해서는 유압 모터의 상태 및 부하의 정보를 알아야 한다. 상태 및 부하의 정보를 추정 하기 위하여 high gain observer를 제안하였다. High gain observer을 사용함으로서 유압 모터와 부하의 동역학의 비선형성을 줄여 상태 및 부하를 효과적으로 추정 하였다. 유압 모터의 위치 제어 성능 및 부하의 관측 능력 평가를 위하여 Matlab/Simulink를 이용하여 모의 실험을 구현 하였다.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.2
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• pp.176-184
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• 2001

The VDC(Vehicle Dynamics Control) is a control system whose target is to improve vehicle stability under critical motion. The system has a good potential of becoming a standard active safety unit in passenger vehicles since it can be implemented on top of the ABS/TCS system with little extra cost. This, however, is possible only when the signals that the VDC system demands can be obtained with sufficient accuracy. In this research, estimators for the road friction coefficient and body sideslip angle have been designed. The two variables have great influence upon performance of the VDC system but not directly measurable. For the estimator design, the Newton method and the nonlinear observer theory have been exploited. The performance of the estimator have been verified via simulations on critical driving conditions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.3
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• pp.275-282
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• 2015

Recently, Vecna BEAR type robot to save injured individuals from inaccessible areas has been developed to minimize the loss of life. Because this robot is driven on rough terrain, there is a risk of rollover and vibration, which could impact the injured. In order to guarantee its stability, an algorithm is required that can estimate the speed limits for various environments in real time. Therefore, a dynamic model for real-time analysis is needed for this algorithm. Because the tracks used as the driving component of Vecna BEAR type robot consist of many parts, it is impossible to analyze the multibody tracks in real time. Thus, a lumped track model that satisfies the requirements of a short computation time and adequate accuracy is required. This study performed lumped track modeling, and the traction force was verified using RecurDyn, which is a dynamic commercial program.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1674-1678
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• 2008

본 연구에서는 심장의 세포 변화에서부터 혈류 순환의 시스템 변화까지 일련의 과정을 시뮬레이션 할 수 있는 통합모델을 개발하였다. 본 통합 모델을 이용하여 대동맥의 탄성도 변화 따른 Pulse Wave Velocity를 추정하였으며 심근의 수축 Mechanics의 변화를 시뮬레이션 하였다. 심장은 단순한 구 형상으로 모델링 되었다. 특히 동맥순환의 특성인 Wave propagation 과 Wave deflection의 현상을 모델링하기 위해 기존 모델에서 사용된 동맥계 순환 모델을 수정하였다. 즉 기존의 동맥 모델을 1차원의 운동방정식과 연속방정식을 기반으로 하는 Distributed arterial model로 대체하였다. Distributed arterial model은 혈액의 점성에 의한 에너지 손실, 혈관의 점탄성 효과 그리고 분지 되는 혈관에서의 에너지 손실을 포함하는 정교한 동맥 순환 모델이다. 정교한 동맥계 순환 모델의 동맥 탄성도 값을 조절함으로써 탄성도 변화에 대한 PWV를 계산 할 수 있었다. 이러한 수치적 방법을 사용하여 노화에 따른 동맥벽 탄성도의 저하가 심근세포의 Cross-bridge 동역학에 미치는 영향을 시뮬레이션 하였다.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.53-60
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• 2018

In this paper, we described the unknown parameter identification using Dual Extended Kalman Filter for precise control of 2-link manipulator. 2-link manipulator has highly non-linear characteristic with changed parameter thought tasks. The parameter kinds of mass and inertia of system is important to handle with the manipulator robustly. To solve the control problem by estimating the state and unknown parameters of the system through the proposed method. In order to verify the performance of proposed method, we simulate the implementation using Matlab and compare with results of RLS algorithm. At the results, proposed method has a better performance than those of RLS and verify the estimation performance in the parameter estimation.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.4
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• pp.190-200
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• 1996

Step-by-step time integration methods are widely used for solving structural dynamics problem. One difficult yet critical choice an analyst must make is to decide an appropriate time step size. The choice of time step size has a significant effect on solution accuracy and computational expense. The objective of this research is to derive error estimate for newly developed time integration method and develop automatic time step size control algorithm for structural dynamics. A formula for computing error tolerance is derived based on desired period resolution. An automatic time step size control strategy is proposed based on a normalized local error estimate for the generalized-α method. Numerical examples demonstrate the developed strategy satisfies general design criteria for time step size control algorithm for dynamic problem.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.227-232
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• 2004

Vehicle dynamics control systems are complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed supplies good results in normal conditions. But the estimation error in severe braking is discontented In this paper, we estimate the absolute vehicle speed of UCT(Unmanned Container Transporter) by using the wheel speed data from standard anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used 10 algorithms are verified experimentally to estimate the absolute vehicle speed and one of them is perfectly shown to estimate the vehicle speed within 4％ error during a braking maneuver.