• Journal of Information Processing Systems
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• 제18권4호
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• pp.457-469
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• 2022

Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of low-temperature frost damage, during drying and wetting cycles, and salt erosion, so the study of concrete deterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus (RDEM) of four different kinds of modified concrete under the special environment in the northwest of China was established using Grey residual Markov theory. Based on the available test data, modified values of the dynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model, combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. The computational analysis showed that the maximum relative error of the corrected dynamic elastic modulus was significantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the model was more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error was significantly lower than that of the rest of the groups. The analysis of the data for each group proved that the model could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as well as the number of cycles when the concrete reached the damaged state.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.28-28
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• 2000

Low-cost solid-state inertial sensors of three rate Gyroscopes and a triaxial Accelerometer are evaluated in static and dynamic environments. As a interim result, error models of each inertial sensors are generated. Model parameters with respect to temperature are acquired in static environment. These error models are included in an Extended Kalman Filter(EKF) to compensate bias error due to temperature variation. Experimental results in dynamic environment are included to show the validity of the each error model and the performance improvement of a compensated low cost inertial sensors for a navigational application

• 드라이브 ㆍ 컨트롤
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• 제17권1호
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• pp.44-50
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• 2020

For the requirement of accurate tracking control and the safety of physical human-robot interaction, torque control is basically desirable for humanoid robots. Because of the complexity of humanoid robot dynamics, the TDC (time-delay control) is practical because it does not require a dynamic model. However, there occurs a considerable error due to discontinuous non-linearities. To solve this problem, the TDC-FLC (fuzzy logic compensator) is applied to humanoid robots. The applied controller contains three factors: a TDE (time-delay estimation) factor, a desired error dynamic factor, and FLC to suppress the TDE error. The TDC-FLC is easy to execute because it does not require complicated humanoid dynamic calculations and the heuristic fuzzy control rules are intuitive. TDC-FLC is implemented on the whole body of a humanoid, not on biped legs even though it is performed by a virtual humanoid robot. The simulation results show the validity of the TDC-FLC for humanoid robots.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.530-533
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• 1993

This paper describes a new method of dynamic error compensation, using a digital convolution integrator and two digital low pass filters. In this method, the process of compensation consists of three steps. First, sampling and digitizing of input signal, second, removing the noise in sampled data by the low pass filter and third, making a convolution integral using the output data of low pass filters. This method showed a good experimental result of reducing dynamic error even if there was a slight noise in the input signal. As a result, the detecting time constant of resistance thermo-bulb was improved to about 1/10th.

• 한국정밀공학회지
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• 제24권12호
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• pp.57-64
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• 2007

There have been many researches for optimal controllers in multivariable systems, and they generally use accurate linear models of the plant dynamics. Real systems, however, contain nonlinearities and high-order dynamics that may be difficult to model using conventional techniques. Therefore, it is necessary a PID gain tuning method without explicit modeling for the multivariable plant dynamics. The PID tuning method utilizes the sign of Jacobian and gradient descent techniques to iteratively reduce the error-related objective function. This paper, especially, focuses on the role of I-controller when there is a steady state error. However, it is not easy to tune I-gain unlike P- and D-gain because I-controller is mainly operated in the steady state. Simulations for an overhead crane system with dynamic friction show that the proposed PID-LC algorithm improves controller performance, even in the steady state error.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.189-191
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• 2006

This paper analyzes effect of the spinning vehicle on the GPS signal. In rapid spinning vehicles such as missiles and space rockets, carrier phase and frequency depend on the roll rate of the vehicle. It induces phase and frequency modulation caused by the roll rate. The modulated phase and frequency increase dynamic stress error of the tracking loop. Even though higher order tracking loop can remove dynamic stress error, the dynamic stress error can not be remove in this case. In order to analyze the effect of the spinning vehicle on the GPS signal, the experiments are carried out. The experiment results show the modulation of the carrier frequency and phase caused by the roll rate of the spinning vehicle.

• Journal of Advanced Marine Engineering and Technology
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• 제20권3호
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• pp.286-286
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Journal of Advanced Marine Engineering and Technology
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• 제20권3호
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• pp.154-161
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• 한국정밀공학회지
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• 제11권6호
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• pp.50-56
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• 1994

A DC generator control system was designed to control the torque of a rotating shaft precisely. The control system is composed of a strain gage type torque cell, a torque cell amplifier, a computer, a D/A converter, a error detector, a DC voltage amplifier and a resistor. The response test under unit step input and the dynamic stability test for the designed control system were carried out. It was confirmed that the settling time from the response test is about 4 s and the error from the dynamic stability test is less than 0.06% of rated output of torque cell. The designed control system may be used to control a DC generator which may be used to apply torque to a rotating shaft.

• 전기전자학회논문지
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• 제14권2호
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• pp.90-97
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• 2010

본 논문에서는 DT-CMOS(Dynamic Threshold voltage CMOS) 스위칭 소자와 DTMOS Error Amplifier를 사용한 고 효율 전원 제어 장치(PMIC)를 제안하였다. 높은 출력 전류에서 고 전력 효율을 얻기 위하여 PWM(Pulse Width Modulation) 제어 방식을 사용하여 PMIC를 구현하였으며, 낮은 온 저항을 갖는 DT-CMOS를 설계하여 도통 손실을 감소시켰다. 벅 컨버터(Buck converter) 제어 회로는 PWM 제어회로로 되어 있으며, 삼각파 발생기, 밴드갭 기준 전압 회로, DT-CMOS 오차 증폭기, 비교기가 하나의 블록으로 구성되어 있다. 제안된 DT-CMOS 오차증폭기는 72dB DC gain과 83.5위상 여유를 갖도록 설계하였다. DTMOS를 사용한 오차증폭기는 CMOS를 사용한 오차증폭기 보다 약 30%정도 파워 소비 감소를 보였다. Voltage-mode PWM 제어 회로와 낮은 온 저항을 스위칭 소자로 사용하여 구현한 DC-DC converter는 100mA 출력 전류에서 95%의 효율을 구현하였으며, 1mA이하의 대기모드에서도 높은 효율을 구현하기 위하여 LDO를 설계하였다.