• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.117-122
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• 1998

A servo system requires faster and more accurate dynamic reponses. Generally a PD control is mainly used to obtain the precision, and in the other hand a fuzzy control to improve the transient response and to cope with the nonlinearity of systems. Recently hybrid control, which is attempted to combine the advantages of PD control and a Fuzzy control was proposed, but this technique requires complicate design procedures. Therefore in this paper, designed on the Fuzzy controller with a various series rules, width of membership functions. And also it was showed to have the excellent adaptive performances against disturbances and the usefulness of this controller from the results of simulations.

• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.70-71
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• 2017

This paper presents a new cascaded boost multilevel converter topology for distributed generation (DG) systems. Most of DG systems, such as photovoltaic (PV), wind turbine and fuel cells, normally require the complex structure power converters, which makes the system expensive, complex and hard to control. However, the proposed converter topology can generate a much higher output voltage just by using the standard low-voltage switch devices and low voltage DC-sources in a simplified structure, also enhancing the reliability of the switch devices. Simulation and experimental results with a 1.2kW system are presented to validate the proposed topology and control method.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.6
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• pp.335-344
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• 2011

The Tire Pressure Monitoring System(TPMS) is often used recently. However, the standards and functions are very different. Even though the regulation requires all vehicles install the TPMS, there is no a standard of a Physical and Media access control protocol which provides compatibility with other systems. In this paper, we propose a MAC protocol based on the international standard and an energy efficient hybrid RF system platform. The MAC protocol provides compatibility of the TPMS with other systems and the RF system platform reduces energy consumption significantly.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1301-1306
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• 2018

Artificial intelligence is one of the key technologies of the Fourth Industrial Revolution. This paper introduces the diverse kinds of approaches to subjects that tackle diverse kinds of research fields such as model-based MS approach, deep neural network model, image edge detection approach, cross-layer optimization model, LSSVM approach, screen design approach, CPU-GPU hybrid approach and so on. The research on Superintelligence and superconnection for IoT and big data is also described such as 'superintelligence-based systems and infrastructures', 'superconnection-based IoT and big data systems', 'analysis of IoT-based data and big data', 'infrastructure design for IoT and big data', 'artificial intelligence applications', and 'superconnection-based IoT devices'.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.153-164
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• 2021

The increasing importance of such fields as embedded systems, pervasive computing, and hybrid systems control is increasing attention to the time-dependent aspects of system modeling. In this paper, we focus on modeling conceptual time. Conceptual time is time represented in conceptual modeling, where the notion of time does not always play a major role. Time modeling in computing is far from exhibiting a unified and comprehensive framework, and is often handled in an ad hoc manner. This paper contributes to the establishment of a broader understanding of time in conceptual modeling based on a software and system engineering model denoted thinging machine (TM). TM modeling is founded on a one-category ontology called a thimac (thing/machine) that is used to elaborate the design and analysis of ontological presumptions. The issue under study is a sample of abstract modeling domains as exemplified by time. The goal is to provide better understanding of the TM model by supplementing it with a conceptualization of time aspects. The results reveal new characteristics of time and related notions such as space, events, and system behavior.

• Earthquakes and Structures
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• v.23 no.4
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• pp.329-338
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• 2022

This work addresses the optimization controller design problem combining the AI evolution bat (EB) optimization algorithm with a fuzzy controller in the practical application of a reinforced concrete frame structure. This article explores the use of an intelligent EB strategy to reduce the dynamic response of Lead Rubber Bearing (LRB) composite reinforced concrete frame structures. Recently developed control units for plant structures, such as hybrid systems and semi-active systems, have inherently non-linear properties. Therefore, it is necessary to develop non-linear control methods. Based on the relaxation method, the nonlinear structural system can be stabilized by properly adjusting the parameters. Therefore, the behavior of a closed-loop system can be accurately predicted by determining the behavior of a closed-loop system. The performance and durability of the proposed control method are demonstrated by numerical simulations. The simulation results show that the proposed method is a viable and feasible control strategy for seismically tuned composite reinforced concrete frame structures.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.801-805
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• 2008

Today, hydraulic systems play an important role in modern industry for the reasons that hydraulic actuator systems take many advantages over other technologies with high durability and the ability to produce large forces at high speeds. In recent years, electro-hydraulic actuator systems, which combine electric and hydraulic technology into a compact unit, have been adapted to a wide variety of force, speed and torque requirements. Moreover these systems resolve energy consumption and noise problems characteristic existed in the conventional hydraulic systems. Therefore, these systems have a wide range application fields especially in an excavator. So the purpose of this paper is to demonstrate efficiency of the energy saving and present some control algorithms which apply to electro-hydraulic actuator system in the bucket of the excavator. Experiments are carried out to verify the effectiveness of the proposed system with various external loads as in real working conditions.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.445-452
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• 2019

In this study, parallel processing codes of k-means clustering algorithm were developed and implemented in a PC-cluster for unsupervised classification of large satellite images. We implemented intra-node code using multicores of CPU (Central Processing Unit) based on OpenMP (Open Multi-Processing), inter-nodes code using a PC-cluster based on message passing interface, and hybrid code using both. The PC-cluster consists of one master node and eight slave nodes, and each node is equipped with eight multicores. Two operating systems, Microsoft Windows and Canonical Ubuntu, were installed in the PC-cluster in turn and tested to compare parallel processing performance. Two multispectral satellite images were tested, which are a medium-capacity LANDSAT 8 OLI (Operational Land Imager) image and a high-capacity Sentinel 2A image. To evaluate the performance of parallel processing, speedup and efficiency were measured. Overall, the speedup was over N / 2 and the efficiency was over 0.5. From the comparison of the two operating systems, the Ubuntu system showed two to three times faster performance. To confirm that the results of the sequential and parallel processing coincide with the other, the center value of each band and the number of classified pixels were compared, and result images were examined by pixel to pixel comparison. It was found that care should be taken to avoid false sharing of OpenMP in intra-node implementation. To process large satellite images in a PC-cluster, code and hardware should be designed to reduce performance degradation caused by file I / O. Also, it was found that performance can differ depending on the operating system installed in a PC-cluster.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.1-6
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• 2002

Many customers consult the Internet before making purchase goods and using contents. The systems in the Internet could store a lot of data and classify the data into information to get relationship between a company and customers. To do that, let's consider a knowledge-assisted hybrid system that utilizes individually a customer's preference to make an optimal solution in the his/her decision making. The knowledge made by using the preference is employed to select an domain set appropriate to him/her business, and the process of selecting definitely provides the customer some benefits: elimination of discomfort from unknown information and reduction of costs and search time for forming an suitable domain set. To effectively adopt individual customer's preference and actively adapt change of business situation, this study propose an architecture of the system which includes rule presentations and an inference engine, and integrates a knowledge-based component into a quadratic programming component. In the experimental results, it is found that a knowledge-assisted hybrid system implemented by this idea is more flexible than existing systems in extension of knowledge about an customer's preference and goes beyond the traditional models.