• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.1-9
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• 2019

In this paper, we propose a Small Active Command scheme which reduces the power consumption of the command bus to DRAM. To do this, we target the ACTIVE command, which consists of multiple packets, containing the row address that occupies the largest size among the addresses delivered to the DRAM. The proposed scheme identifies frequently referenced row addresses as Hot pages first, and delivers index numbers of small caches (tables) located in the memory controller and DRAM. I-ACTIVE and I-PRECHARGE commands using unused bits of existing DRAM commands are added for index number transfer and cache synchronization management. Experimental results show that the proposed method reduces the command bus power consumption by 20% and 8.1% on average in the close-page and open-page policies, respectively.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.129-143
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• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• ETRI Journal
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• v.41 no.2
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• pp.197-206
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• 2019

Software-defined networking (SDN) is a modern approach for current computer and data networks. The increase in the number of business websites has resulted in an exponential growth in web traffic. To cope with the increased demands, multiple web servers with a front-end load balancer are widely used by organizations and businesses as a viable solution to improve the performance. In this paper, we propose a load-balancing mechanism for SDN. Our approach allocates web requests to each server according to its response time and the traffic volume of the corresponding switch port. The centralized SDN controller periodically collects this information to maintain an up-to-date view of the load distribution among the servers, and incoming user requests are redirected to the most appropriate server. The simulation results confirm the superiority of our approach compared to several other techniques. Compared to LBBSRT, round robin, and random selection methods, our mechanism improves the average response time by 19.58%, 33.94%, and 57.41%, respectively. Furthermore, the average improvement of throughput in comparison with these algorithms is 16.52%, 29.72%, and 58.27%, respectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1595-1601
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• 2018

The biggest obstacle to the commercialization of small and medium size microgrid (MG) is the reliability and economics of MG operation and maintenance. In this paper, we propose an autonomous operation method that is implemented as an application program installed in the MG operating system in emergency situations. The proposed algorithm consists of four steps of distinction, recognition, determination and control of emergency situations that can occur in MG. A fuzzy-based situation decision algorithm has been proposed to eliminate the barriers of autonomous operation in actual emergency situation such as occurrence of bad data and communication delay. In addition, countermeasures have been suggested for cases where multiple emergency situations have occurred in combination. The proposed algorithm was tested in a 500kW actual microgrid site of a university. Through the test, the validity of the proposed method and its applicability to practical MG operation are verified.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.10
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• pp.1-7
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• 2020

In this study, a multichannel gas-liquid microextraction system is designed by integrating the automatic elution of extraction line and multichannel gas-purging liquid phase microextraction. The system uses an injection pump and inert gas to push the extraction solvent to a sample bottle of a gas-phase color autosampler and then implements multichannel gas-liquid microextraction and gas chromatography-mass spectrometry. The system also employs a three-way integrated micro-high-temperature heater, syringe pump, and microflow controller to realize the simultaneous processing of multiple groups of samples, thus improving the sample pretreatment speed and reproducibility and reducing human error. Autoinjection experiments were implemented with polycyclic aromatic hydrocarbon standard samples. The experiments show that the average recovery rate of the system exceeds 70%, and the relative standard among the channels is less than 15%.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.3
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• pp.192-199
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• 2022

In DC distribution systems, a TAB converter employing multiple transformers is one of the most widely used topologies due to its high power density, modularizability, and cost-effectiveness. However, the conventional control technique for a grid-connected mode in the TAB converter cannot maintain its reliability for an islanding mode under a blackout situation. In this paper, the islanding mode control technique is proposed to solve this issue. To verify the relative stability and dynamic characteristics of the control technique, small-signal models of both the grid connected and the islanding mode are derived. Based on the small-signal models, PI controllers are designed to provide suitable power control. The proposed control technique, the accuracy of small-signal models, and the performance of the controllers are verified by simulations and experiments with a 1-kW prototype TAB converter.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.59-70
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• 2022

In this paper, we proposed an active fault tolerant control (AFTC) method for the position control of a quadrotor with complete loss of effectiveness of one motor. We obtained the dynamics of a quadrotor using Lagrangian equation without small angle assumption. For detecting the fault on a motor, we designed a fault detection module, which consists of the fault detection and diagnosis (FDD) module and the fault detection and isolation (FDI) module. For the FDD module, we designed a nonlinear observer that observes the states of a quadrotor based on the obtained dynamics. Using the observed states of a quadrotor, we designed residual signals and set the appropriate threshold values of residual signals to detect the fault. Also, we designed an FDI module to identify the fault location using the designed additional conditions. To make a quadrotor track the desired path after detecting the fault of a motor, we designed a fault tolerant controller based on the multiple sliding surface control (MSSC) technique. Finally, through simulations, we verified the effectiveness of the proposed AFTC method for a quadrotor with complete loss of effectiveness of one motor.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.9-16
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• 2023

Robots are expected to expand their scope of application to the military field and take on important missions such as surveillance and enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming for a single robot to be performed more efficiently due to the advantage of having multiple robots. Swarm robots require mutual recognition and collaboration. So they send and receive vast amounts of data, making it increasingly difficult to verify SW. Hardware-in-the-loop simulation used to increase the reliability of mission verification enables SW verification of complex swarm robots, but the amount of verification data exchanged between the HILS device and the simulator increases exponentially according to the number of systems to be verified. So communication overload may occur. In this paper, we propose a digital twin-based communication optimization technique to solve the communication overload problem that occurs in mission verification of swarm robots. Under the proposed Digital Twin based Multi HILS Framework, Network DT can efficiently allocate network resources to each robot according to the mission scenario through the Network Controller algorithm, and can satisfy all sensor generation rates required by individual robots participating in the group. In addition, as a result of an experiment on packet loss rate, it was possible to reduce the packet loss rate from 15.7% to 0.2%.

• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.486-491
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• 2008

This paper describes a model identification method that has been applied to a commercial 12-inch RTP (rapid thermal processing) equipment with an ultimate aim to develop a high-performance advanced controller. Seven thermocouples are attached on the wafer surface and twelve tungsten-halogen lamp groups are used to heat up the wafer. To obtain a MIMO balanced state space model, multiple SIMO (single-input multiple-output) identification with highorder ARX models have been conducted and the resulting models have been combined, transformed and reduced to a MIMO balanced state space model through a balanced truncation technique. The identification experiments were designed to minimize the wafer warpage and an output linearization block has been proposed for compensation of the nonlinearity from the radiation-dominant heat transfer. As a result from the identification at around 600, 700, and $800^{\circ}C$, respectively, it was found that $y=T(K)^2$ and the state dimension of 80-100 are most desirable. With this choice the root-mean-square value of the one-step-ahead temperature prediction error was found to be in the range of 0.125-0.135 K.