• 제어로봇시스템학회논문지
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• 제15권6호
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• pp.590-597
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• 2009

This paper propose a PI controller that maximizes the degree of stability using a stability in a simplified motor model the applies decoupling control. The PI controller gains are directly from the motor parameters, thereby reducing the element of trial and error, and, the Kharitonov equation was used to evaluate the robustness of the gains to changes in the motor parameters. In addition, the system poles are located in the same position, the proposed method can provide a fast response. The effectiveness of the proposed controller is verified by simulation results.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 춘계학술대회 논문집
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• pp.149-156
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• 2003

This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o.f. equations of motion of SAUV in a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass and a depth senor. The error of the estimated position still slowly drifts in horizontal plane about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

• 한국축산시설환경학회지
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• 제8권3호
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• pp.165-170
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• 2002

This study was carried out to measure the 3D-distance of a cow model teat for an application possibility on Robotic Milking System(RMS). A teat recognition algorithm was made to find 3D-distance of the model by using Gonzalrez's theory. Some of the results are as follows. 1 . In the distance measurement experiment on the test board, as the measured length, and the length between the center of image surface and the measured image point became longer, their error values increased. 2. The model teat was installed and measured the error value at the random position. The error value of X and Y coordinates was less than 5㎜, and that of Z coordinates was less than 20㎜. The error value increased as the distance of camera's increased. 3. The equation for distance information acquirement was satisfied with obtaining accurate distance that was necessary for a milking robot to trace teats, A teat recognition algorithm was recognized well four model cow teats. It's processing time was about 1 second. It appeared that a teat recognition algorithm could be used to determine the 3D-distance of the cow teat to develop a RMS.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.179-184
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• 1993

In this paper, an optimal motion control scheme is proposed for robot manipulators. A simple explicit solution to the Hamilton-Jacobi equation is presented. The optimization of motion control is based on the mininization of the torque term affecting the kinetic energy and the augmented error which has the first-order stable dynamics for the position and velocity tracking error. In the presence of parametric uncertainty, an adaptive control scheme using the optimal principle is proposed. The global stability of the closed-loop system is guaranteed by the Lyapunov stability approach, The effectiveness and feasibility of the proposed control schemes are shown by simulation results.

• Structural Engineering and Mechanics
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• 제2권3호
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• pp.245-256
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• 1994

A new axisymmetric crack model is proposed on the basis of p-version of the finite element method limited to theory of small scale yielding. To this end, axisymmetric stress element is formulated by integrals of Legendre polynomial which has hierarchical nature and orthogonality relationship. The virtual crack extension method has been adopted to calculate the stress intensity factors for 3-D axisymmetric cracked bodies where the potential energy change as a function of position along the crack front is calculated. The sensitivity with respect to the aspect ratio and Poisson locking has been tested to ascertain the robustness of p-version axisymmetric element. Also, the limit value that is an exact solution obtained by FEM when degree of freedom is infinite can be estimated using the extrapolation equation based on error prediction in energy norm. Numerical examples of thick-walled cylinder, axisymmetric crack in a round bar and internal part-thorough cracked pipes are tested with high precision.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.660-664
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• 2003

The optimal thickness distribution of an active damping layer is sought so that it satisfies a certain constraint on the dynamic performance of a system minimizing control efforts. To obtain a topologically optimized configuration, which includes size and shape optimization, thickness of the active damping layer is interpolated using linear functions. With the control energy as the objective function to be minimized, the state error energy is introduced as the dynamic performance criterion for the system and used lot a constraint. The optimal control gains are evaluated from LQR simultaneously as the optimization of the layer position proceeds. From numerical simulation, the topologically optimized distribution of the active damping layer shows the same dynamic performance and cost as the Idly covered counterpart, which is optimized only in terms of control gains, with less amount of the layer.

• 한국통신학회논문지
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• 제34권12B호
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• pp.1387-1398
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• 2009

최근에 이동국(MS)위치에 대한 정확한 위치 추정이 많이 요구되고 있다. 하지만, 기존 방법을 사용한 위치 추정 방법에는 많은 문제를 가지고 있다. 기지국(BS)은 이동국(MS)에서 전파한 전파를 수신하여 시간 지연에 따른 거리를 측정하고, 이동국(MS)에 근접한 기지국(BS)들을 선택하여 기존의 삼각측정법을 사용하여 위치를 추정한다. 이 방법은 참 위치와 추정된 위치가 많은 오차를 보이고 있다. 본 논문은 이동국(MS)의 위치를 추정하기 위해서 주변 기지국(BS)들을 선택하는 방법과 코사인 제 2법칙을 사용하여 각도를 추정하여 이동국(MS)의 위치를 추정하는 방법을 제안한다. 시뮬레이션을 통해서 기존 방법과 제안한 방법의 비교 검토하여 제안한 방법의 우수성을 증명한다.

• 소성∙가공
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• 제27권6호
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• pp.331-338
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• 2018

Electrohydraulic forming (EHF) process is a high speed forming process that utilizes the electric energy discharge in fluid-filled chamber to deform a sheet material. This process is completed in a very short time of less than 1ms. Therefore, finite element analysis is essential to observe the deformation mechanism of the material in detail. In addition, to perform the numerical simulation of EHF, the material properties obtained from the high-speed status, not quasi static conditions, should be applied. In this study, to obtain the parameters in the constitutive equation of Al 6061-T6 at high strain rate condition, a surrogate model using an artificial neural network (ANN) technique was employed. Using the results of the numerical simulation with free-bulging die in LS-DYNA, the surrogate model was constructed by ANN technique. By comparing the z-displacement with respect to the x-axis position in the experiment with the z-displacement in the ANN model, the parameters for the smallest error are obtained. Finally, the acquired parameters were validated by comparing the results of the finite element analysis, the ANN model and the experiment.

• 제어로봇시스템학회논문지
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• 제22권9호
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• pp.716-722
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• 2016

Coordinate estimation is an essential function for autonomous navigation of a mobile robot. The optical mouse sensor is convenient and cost-effective for the coordinate estimation problem. It is possible to overcome the position estimation error caused by the slip and the model mismatch of robot's motion equation using the optical mouse sensor. One of the simple methods for the position estimation using the optical mouse sensor is integration of the velocity data from the sensor with time. However, the unavoidable noise in the sensor data may deteriorate the position estimation in case of the simple integration method. In general, a mobile robot has ready-to-use motion information from the encoder sensors of driving motors. By combining the velocity data from the optical mouse sensor and the motion information of a mobile robot, it is possible to improve the coordinate estimation performance. In this paper, a coordinate estimation algorithm for an autonomous mobile robot is presented based on the well-known Kalman filter that is useful to combine the different types of sensors. Computer simulation results show the performance of the proposed localization algorithm for several types of trajectories in comparison with the simple integration method.

• 한국항해학회지
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• 제23권3호
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• pp.35-44
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• 1999

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.