• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.524-529
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• 2004

In this paper, We described the method which developed the optimal control system for air separation unit to change production rates frequently and rapidly. Control models of the process were developed from actual plant data using subspace identification method which is developed by many researchers in resent years. The model consist of a series connection of linear dynamic block and static nonlinear block (Wiener model). The model is controlled by model based predictive controller. In MPC the input is calculated by on-line optimization of a performance index based on predictions by the model, subject to possible constraints. To calculate the optimal the performance index, conditions are expressed by LMI(Linear Matrix Inequalities).In order to access at the Bailey DCS system, we applied the OPC server and developed the Client program. The OPC sever is a device which can access Bailey DCS system.The Client program is developed based on the Matlab language for easy calculation,data simulation and data logging. Using this program, we can apply the optimal input to the DCS system at real time.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.1
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• pp.18-26
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• 2017

This paper proposes the model predictive control with space vector modulation (SVM) method for current control of voltage-source inverter. Unlike the conventional method using a limited number of voltage vectors by switching states, the proposed method can consider various voltage vectors to identify the optimized voltage vector. The various voltage vectors are obtained by subdividing existing voltage vectors. The optimized voltage vector that minimizes the cost function is selected and applied to the inverter by using the SVM. The various voltage vectors and SVM reduce current ripples in the output AC side of the inverter compared with the conventional method. The effectiveness and performance of the proposed method are verified through simulation and experiment with a three-phase two-level voltage-source grid-connected inverter.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.742-751
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• 2018

Electric vehicles (EV) are emerging as the future transportation vehicle reflecting their potential safe environmental advantages. Vehicle to Grid (V2G) system describes the hybrid system in which the EV can communicate with the utility grid and the energy flows with insignificant effect between the utility grid and the EV. The paper presents an optimal power control and energy management strategy for Plug-In Electric Vehicle (PEV) charging stations using Wind-PV-FC-Battery renewable energy sources. The energy management optimization is structured and solved using Multi-Objective Particle Swarm Optimization (MOPSO) to determine and distribute at each time step the charging power among all accessible vehicles. The Model-Based Predictive (MPC) control strategy is used to plan PEV charging energy to increase the utilization of the wind, the FC and solar energy, decrease power taken from the power grid, and fulfil the charging power requirement of all vehicles. Desired features for EV battery chargers such as the near unity power factor with negligible harmonics for the ac source, well-regulated charging current for the battery, maximum output power, high efficiency, and high reliability are fully confirmed by the proposed solution.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.2
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• pp.45-52
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• 2019

BEMS(Building Energy Management Systems) have been applied to office buildings and collect relevant building energy data, e.g. temperatures, mass flow rates and energy consumptions of building mechanical systems and indoor spaces. The aforementioned measured data can be beneficially utilized for developing data-driven machine learning models which can be then used as part of MPC(Model Predictive Control) and/or optimal control strategies. In this study, the authors developed ANN(Artificial Neural Network) models of an AHU (Air Handling Unit) and a chiller for a real-life office building using BEMS data. Based on the ANN models, the authors developed optimal control strategies, e.g. daily operation schedule with regard to optimal start and stop of the AHU and the chiller (500 RT). It was found that due to the optimal start and stop of the AHU and the chiller, 4.5% and 16.4% of operation hours of the AHU and the chiller could be saved, compared to an existing operation.

• Journal of IKEEE
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• v.24 no.1
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• pp.147-153
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• 2020

Conventional lane detection algorithms have problems in that the detection rate is lowered in road environments having a large change in curvature and illumination. The probabilistic Hough transform method has low lane detection rate since it exploits edges and restrictive angles. On the other hand, the method using a sliding window can detect a curved lane as the lane is detected by dividing the image into windows. However, the detection rate of this method is affected by road slopes because it uses affine transformation. In order to detect lanes robustly and avoid obstacles, we propose driving assist system using semantic segmentation based on deep learning. The architecture for segmentation is SegNet based on VGG-16. The semantic image segmentation feature can be used to calculate safety space and predict collisions so that we control a vehicle using adaptive-MPC to avoid objects and keep lanes. Simulation results with CARLA show that the proposed algorithm detects lanes robustly and avoids unknown obstacles in front of vehicle.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1858-1865
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• 2007

In this paper, we introduce the design and implementation of satellite IP modem. The designed satellite IP modem shows the performance of 0.2% overhead, BER=10-5 when Eb/No=6dB, frequency offset of 8KHz, data rate up to 1536Kbps, $F_{if}=140MHz$. The designed system is verified through software simulation and then implemented with MPC86x communication processor, TMS320C6416 DSP, and Altera FPGA. Since each hardware unit is implemented in daughter board for modularity, we can reduce the development time and easily improve the performance with using better processor. Linux is used for embedded OS because it shows better performance in IP manipulation multitask processing, and hardware control through device driver. The implemented system is tested and verified with channel simulator. Since the proposed IP modem shows small size and light weight, that can be used anywhere with easy if you need IP environment.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.75.2-75.2
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• 2019

Low surface brightness (LSB) dwarf galaxies hold a key to resolve the small-scale problems of Lambda Cold Dark Matter (LCDM) paradigm such as missing satellites problem. Many recent studies found LSB dwarf galaxies around massive galaxies beyond Local Group up to 10Mpc. Motivated by this, we can increase the number of them by searching for LSB dwarf galaxies around galaxies up to 40Mpc. We use stacked deep (${\mu}_R{\sim}26.2mag\;arcsec^{-2}$) optical B, R-band images taken from Maidanak 1.5m telescope, one of facilities of Intensive Monitoring Survey of Nearby Galaxies (IMSNG) which monitored nearby galaxies in a day cadence from 2014 to 2016. Extended LSB sources in ambient regions of 16 nearby galaxies are selected using central surface brightness and total R magnitude criteria. After that, 24 LSB dwarf candidates are selected with visual inspection. To identify if the candidates are satellites or not, we are trying to compare the number density of LSB dwarf candidates around massive galaxies with those in Canada-France-Hawaii-Telescope Legacy Survey (CFHTLS) wide fields which have no dominant massive galaxies for control sample.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.30-36
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• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.1
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• pp.35-41
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• 2010

In developing modern aircraft, the reconfiguration control that can improve the safety and the survivability against the unexpected failure by partitioning control surfaces into several parts has been actively studied. This paper deals with the reconfiguration control using model predictive control method considering the saturation of control surfaces under the control surface failure. Linearized aircraft model at trim condition is used as the internal model of model predictive control. We propose the controller that performs optimization using LMI (linear matrix inequalities) based semi-definite programming in case that control surface saturation occurs, otherwise, uses analytic solution of the model predictive control. The performance of the proposed control method is evaluated by nonlinear simulation under the flight scenario of control surface failure.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.536-539
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• 2004

IEEE 802.11 Point Coordination Function (PCF) mode is defined to support time bounded traffic, such as voice in wireless LANs. The poll scheduling plays an important role in IEEE 802.11 PCF mode operation. This paper proposed a Multicast Polling Scheme (MPC) to increase the performance of wireless LANs. Moreover, we proposed a polling schedule scheme for our proposed multi-poll to serve real-time traffic. The results show that the proposed mechanism is more efficient than the original IEEE 802.11 PCF.