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비구조적 불확실성이 존재하는 DC모터에 대한 외란관측기 기반 제어기의 강인성에 대한 연구
조남훈,Jo, Nam-Hoon 대한전기학회 2017 전기학회논문지 Vol.66 No.1
In this paper, we study the robustness of disturbance observer based controller for DC motor in the presence of unmodeled dynamics. It is well known that the robustness property usually becomes weaker as the control gain becomes larger. On the contrary to this expectation, it is shown that the phase margin of DOB controller remains quite a large value even though the time constant of Q-filter becomes smaller. The computer simulation results show that DOB controller is able to stabilize the motor system even in the presence of unmodeled dynamics. On the contrary, the unity-feedback system fails to maintain stability when a high gain feedback is employed for the purpose of achieving better disturbance attenuation performance.
조남훈,Jo, Nam-Hun 한국방위산업진흥회 1994 國防과 技術 Vol.- No.181
새로운 국제질서의 출현은 방위산업분야에도 직접적 영향을 미쳐 각국은 국제적 해방 분위기에 따른 총체적 방산수요감소에 직면하게 되었다. 특히 이러한 현상은 과거 국제질서유지에 중대한 역할을 담당해 온 강대국들에게 더욱 심각하여, 방산기반의 축소 및 민수화를 포함하는 방산구조 재정립 방안을 모색하게 되었다.
조남훈,Jo, Nam-Hun 한국정보통신집흥협회 1998 정보화사회 Vol.124 No.-
벤처사업을 조금 더 자세히 정의한다면 "높은 위험을 무릅쓰고 새로운 아이디어나 기술을 사업화하여 성공할 경우 높은 수익을 기대하는 벤처 비즈니스 와 높은 위험을 알고서도 그 사업에 자금을 투자하는 벤처캐피탈의 결합"이라고 할 수 있다.
신경회로망을 이용한 원전SG 세관 결함패턴 분류성능 향상기법
趙南熏(Nam-Hoon Jo),李享範(Hwang-Beom Lee),韓基元(Ki-Won Han),宋城鎭(Sung-Jin Song) 대한전기학회 2007 전기학회논문지 Vol.56 No.7
In this paper, we study the classification of defects at steam generator tube in nuclear power plant using eddy current testing (ECT). We consider 4 defect patterns of SG tube: Ⅰ-In type, Ⅰ-Out type, Ⅴ-In type, and Ⅴ-Out type. Through numerical analysis program based on finite element modeling, 400 ECT signals are generated by varying width and depth of each defect type. In order to improve the classification performance, we propose new feature extraction technique. After extracting new features from the generated ECT signals, multi-layer perceptron is used to classify the defect patterns. Through the computer simulation study, it is shown that the proposed method achieves 100% classification success rate while the previous method yields 91% success rate.
고속 팬터그래프의 새로운 동적 모형 및 외란관측기를 이용한 제어기 설계
趙南熏(Nam-Hoon Jo),李鋼泫(Kang-Hyun Lee) 대한전기학회 2007 전기학회논문지 Vol.56 No.12
The pantograph-catenary system is one of important components for high-speed rail system that are powered electrically. Electrical power is delivered from a catenary structure to the train via a pantograph and thus it is very important to regulate the contact force between catenary and pantograph. Although a lot of research results for active pantograph have been reported, most of them have made an unrealistic assumption that the catenary displacement is constant with respect to the time. In this paper, we present a new pantograph model that regards the catenary displacement as an unknown disturbance input. Moreover, a disturbance observer based controller is proposed to remove the effect of disturbance, i.e., the catenary displacement variation. The computer simulation result shows that the substantial improvement in regulating the contact force can be achieved by the proposed controller.
무게변동을 고려한 자기부상시스템의 저차 외란관측기 제어기 설계
조남훈(Nam-Hoon Jo) 대한전기학회 2017 전기학회논문지 Vol.66 No.5
In this paper, we design a reduced-order disturbance observer (DOB) controller for an EMS (Electro-Magnetic Suspension) system with mass uncertainty. Compared with conventional DOB controller, the proposed reduced-order DOB controller can be implemented in a simpler way, since it uses reduced order nominal model and Q-filter. It is shown that the nominal model for the proposed DOB controller should be carefully chosen in order to achieve the robust stability in the present of mass uncertainty. Computer simulation results to validate the effectiveness of the proposed DOB controller are included.
국내 PBD기반 피난안전설계를 위한 피난용량 산정에 관한 연구(II) - 멀티플렉스 공간의 재실자밀도 조사 -
조남훈(Jo, Nam-Hun),서동구(Seo, Dong-Goo),황은경(Hwang, Eun-Kyung),황금숙(Hwang, Keum-Suk),권영진(Kwon, Young-Jin) 한국화재소방학회 2008 한국화재소방학회 학술대회 논문집 Vol.2008 No.추계
As the rapid and various changing of social aspects, the structures are getting bigger, higher and more complex. The importance of evacuation is on the rise as increased using frequency of multiplex area and it's high population density. According to the result of a survey with 2 domestic multiplex population density, the maximum was 0.43(人/<TEX>$m^2$</TEX>) and 0.51(人/<TEX>$m^2$</TEX>). considering evacuation dangerousness, the maximum value will be suitable for computation of evacuation capacity and this will be submitted as a basic data for computation of evacuation capacity.
조남훈(Nam-Hoon Jo) 대한전기학회 2021 전기학회논문지 Vol.70 No.12
In this paper, we study the robust stability of closed-loop system with noise reduction-disturbance observer (NR-DOB) when the relative degree of plant is greater than that of nominal model. Compared with the case where the relative degree of plant is the same as that of nominal model, it is shown that the nominal model for NR-DOB controller should be carefully chosen in order to achieve the robust stability. Computer simulation results to confirm the proposed condition are also included.
조기학습정지를 이용한 원전 SG세관 결함크기 예측 신경회로망의 성능 향상
趙南熏(Nam-Hoon Jo) 대한전기학회 2008 전기학회논문지 Vol.57 No.11
In this paper, we consider a performance improvement of neural network for predicting defect size of steam generator tube using early stopping. Usually, neural network is trained until MSE becomes less than a prescribed error goal. The smaller the error goal, the greater the prediction performance for the trained data. However, as the error goal is decreased, an over-fitting is likely to start during supervised training of a neural network, which usually deteriorates the generalization performance. We propose that, for the prediction of an axisymmetric defect size, early stopping can be used to avoid the over-fitting. Through various experiments on the axisymmetric defect samples, we found that the difference between the prediction error of neural network based on early stopping and that of ideal neural network is reasonably small. This indicates that the error goal used for neural network training for the prediction of defect size can be efficiently selected by early stopping.