• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.125-128
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• 1987

We investigate the feedback linearizability of nonlinear discrete-time system s of a specific form, $x_k=G_{u_k}oF(x_k)$ where F is a diffeomorphism and [$G_{u_k}$] forms an one parameter group of diffeomorphisms. This structure represents a class of systems which are state equivalent to linear ones and approximates the sampled data model of a continuous-time system. It is also considered a relationship between linearizability and discretization.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1429-1433
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• 2008

In this paper, we consider the design method of robust guaranteed cost controller for discrete-time singular systems with norm-bounded time-varying parameter uncertainty. In order to get the optimum(minimum) value of guaranteed cost, an optimization problem is given by linear matrix inequality (LMI) approach. The sufficient condition for the existence of controller and the upper bound of guaranteed cost function are proposed in terms of strict LMIs without decompositions of system matrices. Numerical examples are provided to show the validity of the presented method.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.46-51
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• 2017

Recent controller design techniques often discretize the target system and implement a discrete controller that is digitized to match the target system. When constructing such a discrete system, it is necessary to first determine the sampling time. The smaller the sampling time is, the more advantageous it can be made similar to the original system, but the cost is a problem when realizing such a configuration as hardware. On the other hand, the longer the time, the more different the system is from the original system, and eventually the control becomes impossible. In this paper, we consider the above problem and propose a more logical approach to determine the sampling time in the discrete system and investigate the relation with the differential controller. We also apply this process to a nonlinear system called ARAGO disc and verify its validity through computer simulation.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1045-1046
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• 2009

본 논문에서는 이산 이벤트 시뮬레이터인 SMPL을 이용하여 노변 네트워크에서의 데이터 처리에 따르는 데이터 캐쉬 성능분석기를 구현한다. 구현된 성능분석기는 SMPL의 요청 도착과 서비스 사건 처리를 기본 골격으로 하여 실제 차량의 궤적 데이터에 기반한 데이터 요청 생성부와 큐잉 정책과 캐쉬 정책을 선택할 수 있는 정책 처리부 등으로 구성된다. 이 분석기는 서비스율, 해당 정책, 캐쉬의 크기 등의 수행인자를 설정하여 이에 따르는 큐 길이의 분포, 캐쉬의 히트율, 요청 처리시간의 분포 등을 측정할 수 있도록 한다. 추정된 성능 요소를 기반으로 노변 네트워크에 기반한 차량 텔레매틱스 시스템에서 RSU(RoadSide Unit)의 배치, 성능 요구사항 분석, 새로운 큐잉 정책과 캐쉬 정책의 설계 등 다양한 응용이 가능하다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.1
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• pp.52-59
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• 1987

A new on-line estimation algorithm for a time varying time delay is proposed. This algorithm is based on the concept of minimization of prediction error. As only the parameters directly related to the poles and zeros of the process are estimated in the algorithm, persistently exciting condition for the convergence of parameters can be less restrictive. Under some assumptions which is necessary in adaptive control, it is shown that this algorithm estimates time varying time delay accurately. In view of computational burden, this algorithm needs far less amount of calculations than other methods. The larger the time delay is, the more effective this algorithm is . Computer simulation shows good properties of the algorithm. This algorithm can be used effectively in adaptive control of large dead time processes.

• KIISE Transactions on Computing Practices
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• v.22 no.4
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• pp.189-194
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• 2016

A trajectory is the motion path of a moving object. The advances in IT have made it possible to collect an immeasurable amount of various type of trajectory data from a moving object using location detection devices like GPS. The trajectories of moving objects are widely used in many different fields of research, including the geographic information system (GIS) field. In the GIS field, several attempts have been made to automatically generate digital maps of roads by using the vehicle trajectory data. To achieve this goal, the method to cluster the trajectories on the same road is needed. Usually, the $Fr{\acute{e}}chet$ distance measure is used to calculate the distance between a pair of trajectories. However, the $Fr{\acute{e}}chet$ distance measure requires prolonged calculation time for a large amount of trajectories. In this paper, we presented a fast heuristic algorithm to distinguish whether the trajectories are in close distance or not using the discrete $Fr{\acute{e}}chet$ distance measure. This algorithm trades the accuracy of the resulting distance with decreased calculation time. By experiments, we showed that the algorithm could distinguish between the trajectory within 10 meters and the distant trajectory with 95% accuracy and, at worst, 65% of calculation reduction, as compared with the discrete $Fr{\acute{e}}chet$ distance.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.639-648
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• 1997

As the areas of computer application are expanded, the real-time applicition enviroments that must process as many transactions as possible within their deadlines have been increased recently. Conventional disk based databaes system is not appropriate in real-time transaction processing due to delying time for disk I/O processing. When the system is overloaede, the performance of transaction scheduling technique using earliest deadline first deteriorates rapidly because it can assign the highest priority ot a transaction that has already missed or is about to miss tis deadline. Therfore, the performance of suggested transaction secheduling technique is made to improved by propos-ing the doule locking mechanism based on priority. Finally, in order to evaluate the performance of the proposed priority-based double locking techniques under single proessor and main memory database system environments, the simulation model was developed using the SLAM II language.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1819-1820
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• 2006

사다리꼴 역기전력을 갖는 BLDC 모터 제어에 있어서, 전류 맥동의 문제가 가장 심각하다. BLDC 모터 제어의 많은 연구가 이 전류 맥동 문제를 개선하기 위하여 연구되어지고 있다. 맥동의 저감을 위하여 전류 전환 시간동안에 전류 전환시의 보상 PWM 듀티를 인가하는 방법으로 전류의 감쇠/상승 기울기를 같게 하여 맥동을 줄일 수 있는 방법이 연구되었다. 여기서 전류전환 시간을 측정하기 위해서는 전류 전환시작 시점의 상전류를 아는 것이 매우 중요하다. 상 전류를 측정하는 방법으로는 전류센서를 이용하는 방법이 보편적으로 사용되나 저항을 이용한 전류 검출 방법을 사용하면 스위치의 On/Off에 대하여 이산적인 전류를 측정하게 되는 문제점이 있을 수 있다. 다른 방법으로는 전기 모델을 이용하여 전류를 추정함으로서 전류 검출을 대신할 수 있다. 이러한 전류 추정기는 선형 방정식으로 모델을 구성할 수도 있고, 뉴럴네트웍으로 전류모델을 구성할 수도 있다. 선형방정식으로 구하여진 모델은 일반적으로 실제 시스템에 산재되어 있는 비선형 성분들을 모델 내에 포함시킬 수 없다. 본 연구에서는 뉴럴네트웍 모델을 이용하여 안정적이면서 매우 정확한 비선형 모델을 이용하여 비교적 간단한 방법으로 전류를 추정하고 이를 전류 맥동 저감 방법에 적용하여 전류 맥동 보상에 유용함을 보였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.209-216
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• 2012

In this paper, we propose a novel tracking method which uses image features consisted of the area, average intensity, aspect ratio of a target image for the real-time IR surveillance system. The image features of the ground target can be modeled as a random process with exponential autocorrelation function mathematically. Finally, we derived a discrete target dynamic equation including kinematic states and geometric states of the target. Simulation results shows that the performance of the proposed method is better than that of the previous tracking method.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.10
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• pp.723-730
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• 2013

This paper presents the design of an arm gesture recognition system using Kinect sensor. A variety of methods have been proposed for gesture recognition, ranging from the use of Dynamic Time Warping(DTW) to Hidden Markov Models(HMM). Our system learns a unique HMM corresponding to each arm gesture from a set of sequential skeleton data. Whenever the same gesture is performed, the trajectory of each joint captured by Kinect sensor may much differ from the previous, depending on the length and/or the orientation of the subject's arm. In order to obtain the robust performance independent of these conditions, the proposed system executes the feature transformation, in which the feature vectors of joint positions are transformed into those of angles between joints. To improve the computational efficiency for learning and using HMMs, our system also performs the k-means clustering to get one-dimensional integer sequences as inputs for discrete HMMs from high-dimensional real-number observation vectors. The dimension reduction and discretization can help our system use HMMs efficiently to recognize gestures in real-time environments. Finally, we demonstrate the recognition performance of our system through some experiments using two different datasets.