• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.7
• /
• pp.501-508
• /
• 2004

In this paper, a coordinated scheduling algorithm is proposed to reduce end-to-end delay in distributed control of systems. For the algorithm, the analysis of practical end-to-end delay in the worst case is performed priory with considering implementation of the systems. The end-to-end delay is composed of the delay caused by multi-task scheduling of operating systems, the delay caused by network communications, and the delay caused by asynchronous timing between operating systems and network communications. Through some simulation tests based on CAN(Controller Area Network), the proposed worst case end-to-end delay analysis is validated. Through the simulation tests, it is also shown that a real-time distributed control system designed to existing worst case delay cannot guarantee end-to-end time constraints. With the analysis, a coordinated scheduling algorithm is proposed here. The coordinated scheduling algorithm is focused on the reduction of the delay caused by asynchronous timing between operating systems and network communications. Online deadline assignment strategy is proposed for the scheduling. The performance enhancement of the distributed control systems by the scheduling algorithm is shown through simulation tests.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.50 no.11
• /
• pp.520-527
• /
• 2001

This paper suggests a new methodology of evolutionary computations - an Adaptive Evolutionary Algorithm (AEA) for solving the Economic Load Dispatch (ELD) problem which has piecewise quadratic cost functions and prohibited operating zones with many local minima. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and the population by ES are adaptively modulated according to the fitness. Case studies illustrate the superiority of the proposed methods to existing conventional methods in power generation cost and computation time. The results demonstrate that the AEA can be applied successfully in the solution of ELD with piecewise quadratic cost functions and prohibited operating zones

• IEMEK Journal of Embedded Systems and Applications
• /
• v.15 no.6
• /
• pp.289-297
• /
• 2020

Although flash disks are being used widely instead of hard disks, it is difficult to optimize for effective utilization of flash disks because overwrite in place is impossible and the power consumption and time required for read, write, and erase operations are all different. One of these optimization issues is a cache management strategy to minimize write operations. The cache operates at two levels: an operating system equipped with flash disks and a translation layer within the flash disk. Most studies deal with the operating system-level cache strategy. In this study, we implement and analyse the DPW-LRU algorithm which is one of the recently proposed operating system cache replacement algorithms to apply to FTL, and grope with some improvements. As a result of the experiment, the DPW-LRU algorithm maintained superiority even in the FTL environment, and showed better performance with a slight improvement.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.5
• /
• pp.724-729
• /
• 2016

Nowadays high-cost energy storage system using flywheel or secondary battery is applying to hybrid generation system with WT(Wind Turbine) and diesel generator in island areas for stable operation. This paper proposes an operating algorithm and modeling method of the hybrid generation system that can operate for variable wind speed and load, which is composed of energy storage system, variable-speed PMSG(Permanent Magnet Synchronous Generator) WT and diesel generator applied in island areas. Initially, the operating algorithm was proposed for frequency and voltage to be maintained within the proper ranges for load and wind speed changes. Also, the modeling method is proposed for variable speed PMSG WT, diesel generator and BESS(Battery Energy Storage System). The proposed operating algorithm and modeling method were applied to a typical island area. The frequency and voltage was kept within the permissible ranges and the proposed method was proven to be appropriate through simulations.

• Nuclear Engineering and Technology
• /
• v.56 no.7
• /
• pp.2610-2624
• /
• 2024

Liquid metal heat pipes play a critical role in various high-temperature applications, with their optimization being pivotal to achieving optimal thermal performance. In this study, a deep learning based genetic algorithm is suggested to optimize the operating conditions of liquid metal heat pipes. The optimization performance was investigated in both single and multi-variable optimization schemes, considering the operating conditions of heat load, inclination angle, and filling ratio. The single-variable optimization indicated reasonable performance for various conditions, reinforcing the potential applicability of the optimization method across a broad spectrum of high-temperature industries. The multi-variable optimization revealed an almost congruent performance level to single-variable optimization, suggesting that the robustness of optimization method is not compromised with additional variables. Furthermore, the generalization performance of the optimization method was investigated by conducting an experimental investigation, proving a similar performance. This study underlines the potential of optimizing the operating condition of heat pipes, with significant consequences in sectors such as high temperature field, thereby offering a pathway to more efficient, cost-effective thermal solutions.

• Proceedings of the IEEK Conference
• /
• 2004.08c
• /
• pp.477-481
• /
• 2004

High Quality CD, OAT audio requires that large amount of data. Currently, multi channel preference has been rapidly propagated among latest users. The MPEG(Moving Picture Expert Group) is provides data compression technology of sound and image system. The MPEG standard provides multi channel and 5.1 sounds, using the same audio algorithm as MPEG-l. And MPEG-2 audio is forward and backward compatible. The MDCT (Modified Discrete Cosine Transform) is a linear orthogonal lapped transform based on the idea of TDAC(Time Domain Aliasing Cancellation). In this paper, we proposed the micro-program type vector processor architecture a benefit in MDCT/IMDCT of MPEG-II AAC. And it's reduced operating coefficient by overlapped area to bind. To compare original algorithm with optimized algorithm that cosine coefficient reduced $0.5\%$multiply operating $0.098\%$ and add operating 80.58\%$. Algorithm test is used C-language then we designed hardware architecture of micro-programmed method that applied to optimized algorithm. This processor is 20MHz operation 5V.

• Proceedings of the KIEE Conference
• /
• 2015.07a
• /
• pp.958-959
• /
• 2015

This paper proposes adaptive incremental conductance(A-IC) algorithm for maximum power point tracking(MPPT) control of photovoltaic. Conventional Perturbation & Observation(PO) and IC MPPT control algorithm generally uses fixed step size. A small fixed step size will cause the tracking speed to decrease and tracking accuracy of the MPP will decrease due to large fixed step size. Therefore, this paper proposes N-IC MPPT algorithm that adjust automatically step size according to operating conditions. To improve tracking speed and accuracy, when operating point is far from maximum power point(MPP), step size uses maximum value and when operating point is near from MPP, step size uses variable step size that adjust according to slope of P-V curve. The validity of MPPT algorithm proposed in this paper prove through compare with conventional IC MPPT algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.12 no.2
• /
• pp.69-76
• /
• 1998

This paper presents a novel algorithm for determining the optimal operation of a cogeneration plant with back-pressure and extraction-condensing turbine/generators. The proposed algorithm determines the optimum load of boilers and turbine/generators, using only one parameter, the steam mass flow rate, which can be obtained directly from on-line measurement during plant operation. The proposed algorithm consists of the non -linear operating cost function, and its correlated constraints. Furthermore, it has been successfully applied to an actual industrial cogeneration plant, with satisfactory results. Comparison of these results with actual operating data has revealed that using the proposed algorithm results in at least 1.2~4.5[%] operating cost saving, depending on the process steam load. Furthermore the proposed algorithm can be easily installed in a process control computer because the required input data can be easily obtained from information available on-line.n-line.

• Journal of the Institute of Convergence Signal Processing
• /
• v.6 no.1
• /
• pp.23-26
• /
• 2005

This paper describes the algorithm for deciding the status of the operating machines in the power plants. It is very important to decide whether the status of the operating machines is good or not in the industry to protect the accidents of machines and improve the operation efficiency of the plants. There are two steps to analyze the status of the running machines. First, we extract the features from the input original data. Second, we classify those features into normal/abnormal condition of the machines using the wavelet transform and the input RMS vector through the K-means algorithm. In this paper we developed the algorithm to detect the fault operation using the K-means method from the sound of the operating machines.

• Journal of the Society of Naval Architects of Korea
• /
• v.58 no.2
• /
• pp.121-128
• /
• 2021

According to the increasing interest and demand for the Autonomous Surface Vessels (ASV), the autonomous navigation system is being developed such as obstacle detection, avoidance, and path planning. In general, autonomous navigation algorithm controls the ship by detecting the obstacles with various sensors and planning path for collision avoidance. This study aims to construct and prove autonomous algorithm with integrated various sensor using the Robot Operating System (ROS). In this study, the safety zone technique was used to avoid obstacles. The safety zone was selected by an algorithm to determine an obstacle-free area using 2D LiDAR. Then, drift angle of the ship was controlled by the propulsion difference of the port and starboard side that based on PID control. The algorithm performance was verified by participating in the 2020 Korea Autonomous BOAT (KABOAT).