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Tracking Control of IPMSM based on Disturbance Observer
Yongho Jeon,Shinwon Lee 대한전자공학회 2023 IEIE Transactions on Smart Processing & Computing Vol.12 No.6
A state observer was designed to estimate the state variables required to control the speed, position, and current of the rotor shaft of a synchronous motor system with a permanent magnet rotor. When designing a state observer, an output equation is constructed with measurable state variables as output states among state variables. The state vector is estimated by designing the observer using the state equation and output equation, mathematical models of the motor system, and the Luenberger state observer. A PI controller is configured using the desired reference input and the estimated state to follow as feedback. The precise control performance can be obtained by following the reference speed of the motor. The controllers must be able to compensate for load fluctuations, various parameter errors, and model errors. For this purpose, a state observer was designed to estimate the state, including the disturbance using the Luenberger observer. Obtaining a state estimation error and speed tracking error within 0.1 [%] in the steady state was possible after applying the state estimator designed for a one-horsepower class IPMSM to the disturbancecompensated speed controller and current controller.
THE SOC ESTIMATION OF THE LEAD-ACID BATTERY USING KALMAN FILTER
JEON, YONGHO The Korean Society for Computational and Applied M 2021 Journal of applied mathematics & informatics Vol.39 No.5
In general, secondary batteries are widely used as an electric energy source. Among them, the state of energy storage of mobile devices is very important information. As a method of estimating a state, there is a method of estimating the state by integrating the current according to an energy storage state of a battery, and a method of designing a state estimator by measuring a voltage and estimating a charge amount based on a battery model. In this study, we designed the state estimator using an extended Kalman filter to increase the precision of the state estimation of the charge amount by including the error of the system model and having the robustness to the noise.
A Note on Linear SVM in Gaussian Classes
Jeon, Yongho The Korean Statistical Society 2013 Communications for statistical applications and me Vol.20 No.3
The linear support vector machine(SVM) is motivated by the maximal margin separating hyperplane and is a popular tool for binary classification tasks. Many studies exist on the consistency properties of SVM; however, it is unknown whether the linear SVM is consistent for estimating the optimal classification boundary even in the simple case of two Gaussian classes with a common covariance, where the optimal classification boundary is linear. In this paper we show that the linear SVM can be inconsistent in the univariate Gaussian classification problem with a common variance, even when the best tuning parameter is used.
급변 수심 해역의 해수유동 및 수온 변화에 대한 수치모의-키리바시 해역
전용호(Yongho Jeon),홍도웅(Dowoong Hong),김현주(Hyunjoo Kim),김종규(Jonggyu Kim) 한국해양환경·에너지학회 2021 한국해양환경·에너지학회 학술대회논문집 Vol.2021 No.10
키리바시는 태평양 중부에 위치해 있으며, 수심이 10~4000 m의 급경사를 이룬다. 키리바시 주변해역은 대조차가 약 170 cm이며, 조류는 10 cm/s, 하계 표층수온이 약 19 ℃이다. σ-좌표계의 Environmental Fluid Dynamics Code(EFDC) 수치모의시 동일 수층에서 수온의 변화가 크게 나타나는 문제점이 있다. 따라서 본 연구에서 직 레이어링을 Sigma Stretch(SIG)와 Sigma Zed(SGZ)로 수행하였다. SIG 접근법에서 모델 도메인은 다양한 깊이를 계산하기 위해, 층의 두께는 셀마다 다르지만 각 층에 대한 층 수 및 깊이의 비율은 일정하다. SGZ 모델에서는 레이어 수는 모델 도메인에 따라 달라질 수 있도록 수직 레이어링 체계를 수정하였다. SIG 접근법은 밀도 기울기 항에서 압력 구배 오차가 발생하는데, 수치실험 결과에서 수평 압력 구배 오차에 대한 해수유동 및 수온의 변화를 비교하였다. Kiribati is located in the central Pacific Ocean, with 10m to 4000m in depth, and bathymetry has a steep slope. The spring tidal range is about 170 cm, the tidal current is around 10 cm/s, and the surface temperature in the summer is about 19 ℃. In numerical experiment using the σ-coordiante system in EFDC (Environment Fluid Dynamic Code), there was a problem that the water temperature difference was large in the same layer of the coast and the open sea. So vertical layering was performed with Sigma Stretch (SIG) and Sigma Zed (SGZ). In the SIG approach, the model domains calculate the various depths, the thickness of the layers varies from cell to cell, but the ratio of the number of layers and the depth for each layer is constant. In the SGZ model, the vertical layering scheme is modified so that the number of layers can vary depending on the model domain. In the SIG approach, the pressure gradient error occurs in the density gradient term, and the numerical experiment results compare the changes in current and temperature for the pressure gradient error.