• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.435-438
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• 2002

The Objects of this paper are developing and also improving a high-speed driving system of bushless DC motor(BLDCM) with economical and practical performance. Because BLDC motors are manufactured that each motor can create proper torque for their individual purpose, it is difficult to increase over the rated speed when a motor speed (with it's rated road) is reaching to a maximum speed so the motor torque cannot be increased. This paper verifies the effects of Leading Angle Algorithm, that is proposed on this paper, with examining existing methods to maximize the torque of a motor in high-speed driving area. The arithmetic processor for this experiment is TMS320C240 DSP controller that is designed for a special purpose of motor control in Texis Instrument Inc., and the used Inverter is PM10CSJ060, a Intelligent Power Module of Mitsubishi Corporation.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.69-76
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• 2010

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.115-117
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• 2013

수평자세제어에 대한 활용은 다양한 진동이 발생하는 환경에서 정확한 수평제어를 필요로 하는 모든 분야에 활용할 수 있다. 이러한 수평제어에 대한 문제는 다수의 액추에이터(Actuator)를 어떠한 방법으로 제어하는가에 따라 그 성능이 달라지며, 발생한 외란에 대하여 어떠한 방법으로 외란을 계측하고 특성을 분석하는 것이 무엇보다 중요하다. 이러한 비선형성이 강한 수평자세제어에 대하여 인공지능기법인 신경회로망의 학습기능을 활용하여 그 수평자세 제어에 대한 성능을 연구하고 있는 추세에 있다. 본 논문에서는 고속이며 신뢰성을 보장하고 있는 CAN 통신방식을 활용하여 3개의 리니어 액추에이터(Linear Actuator)를 동시에 제어하도록 하고, 플랜트의 기울어진 상태는 자이로센서를 활용하여 플랜트의 상태를 지능적으로 판단하게 하였다. 또한 플랜트에 발행하는 왜란은 수평자세제어를 위한 플랜트 위에 볼(ball)을 놓아 비선형적인 왜란이 발생하도록 하였다. 이러한 왜란에 대하여 영상처리 기법을 활용하여 지능적으로 제어하도록 하여 CAN 통신의 활용성과 영상처리시스템(Image Processing System)의 활용성 및 지능제어의 활용성을 제시하고자 한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.477-486
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• 2016

This paper presents the area classification, identification, and tracking for multiple moving objects with the similar colors. To do this, first, we use the GMM(Gaussian Mixture Model)-based background modeling method to detect the moving objects. Second, we propose the use of the binary and morphology of image in order to eliminate the shadow and noise in case of detection of the moving object. Third, we recognize ROI(region of interest) of the moving object through labeling method. And, we propose the area classification method to remove the background from the detected moving objects and the novel method for identifying the classified moving area. Also, we propose the method for tracking the identified moving object using Kalman filter. To the end, we propose the effective tracking method when detecting the multiple objects with the similar colors. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.127-136
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• 2005

In this paper, a new architecture and comprehensive design methodology of genetically optimized Rule-based Fuzzy Polynomial Neural Networks(gRFPNN) are introduced and a series of numeric experiments are carried out. The architecture of the resulting gRFPNN results from asynergistic usage of the hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks (PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the gRFPNN. The consequence part of the gRFPNN is designed using PNNs. At the premise part of the gRFPNN, FNN exploits fuzzy set based approach designed by using space partitioning in terms of individual variables and comes in two fuzzy inference forms: simplified and linear. As the consequence part of the gRFPNN, the development of the genetically optimized PNN dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gRFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed gRFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.57-66
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• 2022

The Road Management Administration is cracking down on overloaded vehicles by installing low-speed or high-speed WIMs at toll gates and main lines on expressways. However, in recent years, the act of intelligently evading the overloaded-vehicle control system of the Road Management Administration by illegally manipulating the variable axle of an overloaded truck is increasing. In this manipulation, when entering the overloaded-vehicle checkpoint, all axles of the vehicle are lowered to pass normally, and when driving on the main road, the variable axle of the vehicle is illegally lifted with the axle load exceeding 10 tons alarmingly. Therefore, this study developed a technology to detect the state of the variable axle of a truck driving on the road using roadside camera images. In particular, this technology formed the basis for cracking down on overloaded vehicles by lifting the variable axle after entering the checkpoint and linking the vehicle with the account information of the checkpoint. Fundamentally, in this study, the tires of the vehicle were recognized using the Mask RCNN algorithm, the recognized tires were virtually arranged before and after the checkpoint, and the height difference of the vehicle was measured from the arrangement to determine whether the variable axle was lifted after the vehicle left the checkpoint.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.53-69
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• 2003

Many process variables in modem manufacturing processes have influence on quality of products with complicated relationships. Therefore, it is necessary to control multiple quality variables in order to monitor abnormal signals in the processes. This study proposes an integrated procedure of self-organizing map (SOM) neural network and case-based reasoning (CBR) for multivariate process control. SOM generates patterns of quality variables. The patterns are compared with the reference patterns in order to decide whether their states are normal or abnormal using the goodness-of-fitness test. For validation, it generates artificial datasets consisting of six patterns, normal and abnormal patterns. Experimental results show that the abnormal patterns can be detected effectively. This study also shows that the CBR procedure enables to keep Type 2 error at very low level and reduce Type 1 error gradually, and then the proposed method can be a solution fur multivariate process control.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1993-1998
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• 2010

This paper presents an integrated control module for controlling transportation machine and automatic navigation using a combined technology of mobile telematics and transportation machine telematics, i.e. Mobile In Vehicle (MIV). This development includes hardware implementation and its verification of control mechanism applied to vehicle. In particular, the module is designed to be versatile in such a way that it can collect various information and facilitate various options for convenience by supporting existing networks, such as TCP/IP, Wi-Fi and 3G mobile radio networks. The study offers its versatility, intelligence and cost-effectiveness by enabling the module to support network-independent service, whereas conventional modules operate only in a certain network. Based on this module, a multiple of subsequent convenient functions for transportation machine can further be developed for safe and intelligent transportation machines.

• The Journal of Korean Association of Computer Education
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• v.11 no.4
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• pp.71-83
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• 2008

The recent advances of the information technology have motivated lots of research efforts to develop new computer-aided teaching and learning methodologies on various computer science topics, such as data structures, operating system, computer networks, and computer architecture. However, there have been only few studies to educate the database subject although it is one of the most important topics in the computer science. Specifically, among the various issues in the database subject, a learner often suffers to understand the mechanism of the concurrency control and recovery of database transaction in the database because it highly interacts with other functions in the database. Obviously, an intelligent visualization tool can help a learner to understand the process of the concurrency control and the recovery of database transaction. The purpose of this study is to develop an efficient visualization tool which can help users understand the two phase locking protocol (2PLP)-based concurrency control. Specifically, this visualization tool is designed to encourage a users' participation and raise their interest by visualizing the process of transactions and allowing users to specify and manipulate their own transactions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1113-1118
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• 2012

Smart grid and intelligent transportation system draw significant interest since they are considered as one of the green technologies. These systems require a large number of sensors, actuators, and controllers. Also, machine-to-machine (M2M) communications is important because of the automatic control. The LTE-Advanced networks is preparing a set of functions that facilitate the M2M communications, and particularly the development of an efficient call admission control mechanism is critical. A method that groups MTC devices according to QoS constraints and determines the admission depending on the QoS satisfaction is limitedly applied only if the data transmission period and the maximum delay are identical. This paper proposed a call admission control that is free from such limitation and also optimizes the admission process under the certain condition of the transmission period and maximum delay. The theorems regarding the proposed method are presented with the proofs. The simulations confirms its validity and shows it is better in call admission probability than existing works.