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박부견(PooGyeon Park),이원일(Won Il Lee),이석영(Seok Young Lee) 제어로봇시스템학회 2014 제어·로봇·시스템학회 논문지 Vol.20 No.3
This article surveys the control theoretic study on time delay systems. Since time delay systems are infinite dimensional, there are not analytic but numerical solutions on almost analysis and synthesis problems, which implies that there are a tremendous number of approximated solutions. To show how to find such solutions, several results are summarized in terms of two different axes: 1) theoretic tools like integral inequality associated with the derivative of delay terms, Jensen inequality, lower bound lemma for reciprocal convexity, and Wirtinger-based inequality and 2) various candidates for Laypunov-Krasovskii functionals.
Distribution System Dynamic State Estimation via Mathematical Model Based Approach
Chan-eun Park(박찬은),In Seok Park(박인석),PooGyeon Park(박부견) 대한전기학회 2019 전기학회논문지 Vol.68 No.7
Recently, some novel researches regarding the state estimation for power distribution system have been focused on the dynamic state estimation algorithm due to trend abrupt changes in the distribution system such as actions of prosumers. The previous works studied the Kalman filter for nonlinear system such as extended Kalman filter, unscented Kalman filter. They assume that the state transient model follows smoothing model of the previous states. However, it is hard to set the smoothing coefficient for the estimated states. Thus, this paper proposes the mathematical model of state transient model of power distribution system. Based on the proposed mathematical model, extended Kalman filter algorithm is adopted for dynamic state estimation. All jacobian matrices for the extended Kalman filter is derived as a function of system states, and the proposed algorithm is verified by using IEEE 15 test bus.
심전도 신호 분류의 성능 향상을 위한 웨이블렛 변환 잡음제거 알고리즘
박찬(Chan Park),박태수(Taesu Park),곽민선(Minseon Gwak),박부견(PooGyeon Park) 대한전기학회 2021 대한전기학회 학술대회 논문집 Vol.2021 No.10
본 논문에서는 심전도 신호를 활용하여 딥러닝 모델을 학습시키는 과정에서 잡음을 효과적으로 제거하는 알고리즘을 제안한다. 웨이블렛 변환은 신호의 전처리 과정에서 다양한 분야에서 사용되는 방법으로 다중 단계 웨이블렛 변환을 통하여 신호의 특성을 보존하면서 잡음을 제거하여 학습의 성능을 향상 시킬 수 있다. 본 논문에서는 심전도 신호의 특성을 보존할 수 있는 웨이블렛을 찾고 잡음의 영향이 미치는 단계를 선정하여 효과적으로 잡음을 제거하였다. 시뮬레이션을 통해 본 논문에서 제안한 잡음제거 알고리즘이 전통적인 잡음 제거 방식에 비하여 학습을 위한 전처리에 적합하다는 것을 확인하였다.
볼테라 시리즈 입력을 이용한 냉연 산세 라인 산농도 모델 추정
박찬은(Chan Eun Park),송주만(Ju-man Song),박태수(Tae Su Park),노일환(Il-Hwan Noh),박형국(Hyoung-Kuk Park),최승갑(Seung Gab Choi),박부견(PooGyeon Park) 제어로봇시스템학회 2015 제어·로봇·시스템학회 논문지 Vol.21 No.12
This paper deals with estimating the acid concentration of pickling process using the Volterra inputs. To estimate the acid concentration, the whole pickling process is represented by the grey box model consists of the white box dealing with known system and the black box dealing with unknown system. Because there is a possibility of nonlinear term in the unknown system, the Volterra series are used to estimate the acid concentration. For the white box modeling, the acid tank solution level and concentration equations are used, and for the black box modeling, the acid concentration is estimated using the Volterra Least Mean Squares (LMS) algorithm and Least Squares (LS) algorithm. The LMS algorithm has the advantage of the simple structure and the low computation, and the LS algorithm has the advantage of lowest error. The simulation results compared to the measured data are included.