PURPOSES : This study develops a model that can estimate travel speed of each movement flow using deep-learning-based probe vehicles at urban intersections. METHODS : Current technologies cannot determine average travel speeds for all vehicles passing through a specific real-world area under obseravation. A virtual simulation environment was established to collect information on all vehicles. A model estimate turning speeds was developed by deep learning using probe vehicles sampled during information processing time. The speed estimation model was divided into straight and left-turn models, developed as fully-offset, non-offset, and integrated models. RESULTS : For fully-offset models, speed estimation for both straight and left-turn models achieved MAPE within 10%. For non-offset models, straight models using data drawn from four or more probe vehicles achieved a MAPE of less than 15%. The MAPE for left turns was approximately 20%. CONCLUSIONS : Using probe-vehicle data(PVD), a deep learning model was developed to estimate speeds each movement flow. This, confirmed the viability of real-time signal control information processing using a small number of probe vehicles.

In this study, the change in the mold opening stroke of important functional parts according to the 20, 50, 80, and 100% increase in the injection speed of a hydraulic 150 ton hydraulic injection molding machine was studied to verify the accuracy of the injection speed and mold opening stroke and the reproducibility of the standard deviation. The null and alternative hypotheses were confirmed by conducting hypothesis verification according to the experimental condition change using the experimental design method.

Gas turbine engines are widely used as prime movers of generator and propulsion system in warships. This study addresses the problem of designing a DS-based PID controller for speed control of the LM-2500 gas turbine engine used for propulsion in warships. To this end, we first derive a dynamic model of the LM-2500 using actual sea trail data. Next, the PRC (process reaction curve) method is used to approximate the first-order plus time delay (FOPTD) model, and the DS-based PID controller design technique is proposed according to approximation of the time delay term. The proposed controller conducts set-point tracking simulation using MATLAB (2016b), and evaluates and compares the performance index with the existing control methods. As a result of simulation at each operating point, the proposed controller showed the smallest in , which means that the rpm does not change rapidly. In addition, IAE and IAC were also the smallest, showing the best result in error performance and controller effort.

Recently, considerable attention has been given to nickel-based superalloys used in additive manufacturing. However, additive manufacturing is limited by a slow build rate in obtaining optimal densities. In this study, optimal volumetric energy density (VED) was calculated using optimal process parameters of IN718 provided by additive manufacturing of laser powder-bed fusion. The laser power and scan speed were controlled using the same ratio to maintain the optimal VED and achieve a fast build rate. Cube samples were manufactured using seven process parameters, including an optimal process parameter. Analysis was conducted based on changes in density and melt-pool morphology. At a low laser power and scan speed, the energy applied to the powder bed was proportional to and not . At a high laser power and scan speed, a curved track was formed due to Plateau-Rayleigh instability. However, a wide melt-pool shape and continuous track were formed, which did not significantly affect the density. We were able to verify the validity of the VED formula and succeeded in achieving a 75% higher build rate than that of the optimal parameter, with a slight decrease in density and hardness.

This paper describes the design of H-infinity controller for robust control of a DC motor system. The suggested controller can ensure robustness against disturbance and model uncertainty by minimizing H-infinity norm of the transfer function from exogenous input to performance output and applying the small gain theorem. In particular, the controller was designed to reduce the effects of disturbance and model uncertainty simultaneously by formalizing these problems as a mixed sensitivity problem. The validity of the proposed controller was demonstrated by computer simulations and real experiments. Moreover, the effectiveness of the proposed controller was confirmed by comparing its performance with PI controller, which was tested under the same experimental condition as the H-infinity controller.

This paper deals with the disturbance observer (DOB) based sliding mode control (SMC) for a DC motor to control motor rotating speed precisely and to ensure strong robustness against disturbance including load torque and parameter variation. The reason of steady state error in speed on conventional SMC without DOB is analyzed in detail. Especially, the suggested DOB is designed to prevent measuring noise and harmonics caused by derivative operation on rotating speed. The control performance of the DOB based SMC is evaluated by the various simulations. The simulation results showed that the DOB based SMC had more robust performance than the SMC system without DOB. Especially, precise speed control was possible even though motor parameter variation and load torque was added to the system.

The model predictive controller performance of the mobile robot is set to an arbitrary value because it is difficult to select an accurate value with respect to the controller parameter. The general model predictive control uses a quadratic cost function to minimize the difference between the reference tracking error and the predicted trajectory error of the actual robot. In this study, we construct a predictive controller by transforming it into a quadratic programming problem considering velocity and acceleration constraints. The control parameters of the predictive controller, which determines the control performance of the mobile robot, are used a simple weighting matrix Q, R without the reference model matrix Ar by applying a quadratic cost function from which the reference tracking error vector is removed. Therefore, we designed the predictive controller 1 and 2 of the mobile robot considering the constraints, and optimized the controller parameters of the predictive controller using a genetic algorithm with excellent optimization capability.

본 논문은 직류전동기 속도제어를 위해 매트릭스 컨버터의 적용 가능성을 제안한다. 매트릭스 컨버터는 크게 직접 매트릭스 컨버터와 간접 매트릭스 컨버터로 나뉘는데 본 논문에서는 다양한 출력 단을 구성할 수 있어 향후 많은 활용이 예상되는 간접 매트릭스 컨버터를 이용하였다. 제안한 방식은 기존의 방식보다 입력 전류의 파형을 개선하고, 부피가 크고 비용이 많이 들며 수명단축의 원인이 되는 에너지 저장 요소를 가지지 않는 이점이 있다. 시뮬레이션을 통하여 기존 방식과 본 논문에서 제안하는 방식의 특징을 비교 분석하여 제안한 방식의 유효성을 입증하였다. 속도제어, 토크제어, 부하전류제어에서는 유사한 성능을 보이며, 입력전류는 정류단의 스위치를 직접 제어함으로써 정현파와 유사하게 제어되기 때문에 고조파가 크게 감소되었다.

전남 인근해역에서 많이 사용하는 어로 작업에 사용하는 연승기는 전동기와 2개의 디스크 롤러를 결합하여 1톤 미만의 소형 어선에서 많이 활용하고 있다. 연승기의 작업특성상 연승줄을 끌어 올릴 때 많은 부하가 필요하므로 연승기의 전동기도 단방향으로만 속도 조절을 하면 된다. 본 논문에서는 1톤 미만의 어선의 연승기에 주로 사용되는 400W 용량의 직류전동기를 대상으로 제어 회로를 구성하였으며, 연승기 전동기의 단방향 속도제어를 위해 PWM 전용칩, Half bridge driver 및 MOSFET를 이용하여 제어기를 제작하였다. 또한 현재 사용중인 대분분의 연승기에 빠져있는 배터리 잔량표시기, 배터리 과방전 방지 장치 및 배터리 결선 오류 방지기능 등의 보호기능을 부가하여 사용자 편의를 강화하였다. 이로 인해 배터리 전압이 11.5V 이하가 되면 전동기는 자동을 동작을 정지하여 배터리의 과방전을 막을 수 있었고, 어선 작업자의 빈번한 배터리 결선 실수를 방지하여 컨트롤러의 안전한 사용이 가능토록 하였다. 이러한 연승기를 실제 어로 작업에 시험운전결과 매우 양호하게 동작함을 확인할 수 있었다.

Vacuum kinetic spray(VKS) is a relatively advanced process for fabricating thin/thick and dense ceramic coatings via submicron-sized particle impact at room temperature. However, unfortunately, the particle velocity, which is an important value for investigating the deposition mechanism, has not been clarified yet. Thus, in this research, VKS average particle velocities were derived by numerical analysis method(CFD: computational fluid dynamics) connected with an experimental approach(SCM: slit cell method). When the process gas or powder particles are accelerated by a compressive force generated by gas pressure in kinetic spraying, a tensile force generated by the vacuum in the VKS system accelerates the process gas. As a result, the gas is able to reach supersonic speed even though only 0.6MPa gas pressure is used in VKS. In addition, small size powders can be accelerated up to supersonic velocity by means of the drag-force of the low pressure process gas flow. Furthermore, in this process, the increase of gas flow makes the drag-force stronger and gas distribution more homogenized in the pipe, by which the total particle average velocity becomes higher and the difference between max. and min. particle velocity decreases. Consequently, the control of particle size and gas flow rate are important factors in making the velocity of particles high enough for successful deposition in the VKS system.

In the present work, bismuth nanopowders with various particle size distributions were synthesized by controlling argon (Ar) gas flow rate and chamber pressure of a gas condensation (GC) apparatus. From the analyses of transmission electron microscopy (TEM) images and nitrogen gas adsorption results, it was found that as Ar gas flow rate increased, the specific surface area of bismuth increased and the average particles size decreased. On the other hand, as the chamber pressure increased, the specific surface area of bismuth decreased and the average particles size increased. The optimum gas flow rate and chamber pressure for the maximized electrochemical active surface area were determined to be 8 L/min and 50 torr, respectively. The bismuth nanopowders synthesized at the above condition exhibit 13.47 of specific surface area and 45.6 nm of average particles diameter.

HDDR treated anisotropic Nd-Fe-B powders have been widely used for the sheet motors and the sunroof motors of hybrid or electric vehicles, due to their excellent magnetic properties. Microstructural alignment of HDDR treated powders are mostly depending on the hydrogen reaction in disproportionation step, so the specific method to control hydrogenation reaction is required for improving magnetic properties. In disproportionation step, hydrogenation pressure and reaction time were controlled in the range of 0.15~1.0 atm for 15~180 min in order to control the micorstructural alignment of phase and, at the same time, to improve remanence of HDDR treated magnet powders. In this study, we could obtain a well aligned anisotropic Nd-Fe-B-Ga-Nb alloy powder having high remanence of 12 kG by reducing hydrogen pressure down to 0.3 atm in disproportionation step.

The W/O emulsion was formed by mixing hydrophobic nonion surfactants of span 80 and tween 60 with kerosine, and by adding sodium silicate aqueous solution. Precipitating the W/O emulsion by sodium bicarbonate resulted in spherical silica particles. Shape and size distribution of silica particles were observed. The particles were spherical and they have narrow size distribution. Particle sizes were 9.29, 7.39 and 5.73 μm at homogenizer speed of 2500, 3000, and 3500 rpm, respectively. The particle size was decreased by increasing agitation speed due to the formation of emulsion droplet. At fixed agitation speed, absorbed paraffin oil weight were measured and the SiO2/Na2O mole ratio effects on particle size were investigated. Particle size was decreased by increasing the mole ratio of SiO2/Na2O.