• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.237-239
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• 1995

The inverter for UPS system is required to satisfy pure sinusoidal output voltage with very low THD(Total Harmonic distortion). This paper proposes a TMS320c31 digital signal processor based predictive instantaneous control scheme of inverter. The proposed scheme is able to satisfy the conditions; high capability, high efficiency, low audible noise and robustness of inverter. The transient state characteristics of proposed inverter has been improved. in case of power failure or recovery, nonlinear load, sudden load change or parameters variations. Finally, the performance of the proposed inverter is shown and discussed by simulation and experiment.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.51-57
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• 1996

An improved predictive current control technique for a zero current switched(ZCS) buck-boost series resonant inverter(SRI) is proposed to overcome the inherent disadvantages such as the uncontrollable large overshoot and the large current ripple. Using the proposed technique, four quadrant operations of the output voltage and current for an uninterrutible power supply(URS) application are guaranteed and the buck-boost operation can also be obtained without an additional bidirectional switch.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.227-233
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• 2021

Predictive maintenance has been one of important applications of data science technology that creates a predictive model by collecting numerous data related to management targeted equipment. It does not predict equipment failure with just one or two signs, but quantifies and models numerous symptoms and historical data of actual failure. Statistical methods were used a lot in the past as this predictive maintenance method, but recently, many machine learning-based methods have been proposed. Such proposed machine learning-based methods are preferable in that they show more accurate prediction performance. However, with the exception of some learning models such as decision tree-based models, it is very difficult to explicitly know the structure of learning models (Black-Box Model) and to explain to what extent certain attributes (features or variables) of the learning model affected the prediction results. To overcome this problem, a recently proposed study is an explainable artificial intelligence (AI). It is a methodology that makes it easy for users to understand and trust the results of machine learning-based learning models. In this paper, we propose an explainable AI method to further enhance the explanatory power of the existing learning model by targeting the previously proposedpredictive model [5] that learned data from a core facility (Hyper Compressor) of a domestic chemical plant that produces polyethylene. The ensemble prediction model, which is a black box model, wasconverted to a white box model using the Explainable AI. The proposed methodology explains the direction of control for the major features in the failure prediction results through the Explainable AI. Through this methodology, it is possible to flexibly replace the timing of maintenance of the machine and supply and demand of parts, and to improve the efficiency of the facility operation through proper pre-control.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.67-68
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• 2015

본 논문에서는 멀티모듈 단상 UPS(Uninterruptible Power Supply) 시스템의 예측 제어기법을 제안한다. 제안한 예측 제어기법은 단상 UPS의 수학적 모델링을 통해 설계되었으며, 전류 예측제어를 통해 모드 절환 시 동특성을 향상시켰다. 제안하는 예측 제어기법은 PSIM 시뮬레이션을 통하여 검증하였다.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.313-314
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• 2019

본 논문은 전력부하 불평형 개선을 위한 전기철도용 전력보상장치의 모델예측 전류제어 알고리즘을 제안하였으며, 시뮬레이션을 통해 단상 3-Level 컨버터의 모델예측 전류제어 알고리즘 성능을 검증하였다.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.6
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• pp.592-600
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• 2000

In this paper, a novel control scheme of three-phase PWM rectifiers using only dc-side sensors is proposed. The phase currents are reconstructed from switching states of the rectifier and the dc output current. For effective current control, the currents are estimated by a predictive state observer. Also, both the phase angle and the magnitude of the source voltage are estimated by controlling the deviation between the model current and the system current to be zero. The validity of the proposed ac phase and current sensorless technique has been verified by experimental results.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.307-310
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• 1999

This paper proposes a novel current control method of three-phase PWM rectifiers without phase current sensors. The features of this method are to reconstruct phase currents by using switching pattern of space vector modulation and to estimate phase currents by a predictive state observer for practical applications. Simulation results show that the performance of the proposed system is nearly the same as that of sensor-based system.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.84-85
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• 2013

본 논문은 스파스 매트릭스 컨버터로 구동되는 유도전동기에 과도응답특성 개선을 위한 모델예측제어 기법을 제안한다. 제안하는 기법은 유도전동기의 파라미터를 이용하여 구한 예측 토크와 자속을 통하여 비용함수를 최소화하는 최적의 스위칭 상태를 결정한다. 시뮬레이션을 통해 제안한 제어 기법의 타당성을 검증한다.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1659-1663
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• 1991

A new control design methodology is presented here which is based on a nonlinear time-series reference model. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible a.c. transmission system (FACTS) with series capacitor power feedback control is studied. A bilinear auto-regressive moving average (BARMA) reference model is identified from system data and the feedback control manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index (J). A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack. These applications are typical of the numerous plants for which nonlinear adaptive control has the potential to provide significant performance improvements. For aircraft control, significant maneuverability gains can provide safer transportation under large windshear disturbances as well as tactical advantages. For FACTS, there is the potential for significant increase in admissible electric power transmission over available transmission lines along with energy conservation. Electric power systems are inherently nonlinear for significant transient variations from synchronism such as may result for large fault disturbances. In such cases, traditional linear controllers may not stabilize the swing (in rotor angle) without inefficient energy wasting strategies to shed loads, etc. Fortunately, the advent of power electronics (e.g., high-speed thyristors) admits the possibility of adaptive control by means of FACTS. Line admittance manipulation seems to be an effective means to achieve stabilization and high efficiency for such FACTS. This results in parametric (or multiplicative) control of a highly nonlinear plant.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.9
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• pp.33-41
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• 2015

To improve the power quality of distributed generation (DG) systems even in the presence of distorted grid condition, dual current control scheme of a grid-connected inverter is proposed. The proposed current control scheme is achieved by decomposing the inverter state equations into the fundamental and harmonic components. The derived models are employed to design dual current controllers. The conventional PI decoupling current controller is used in the fundamental model to control the main power flow in DG systems. At the same time, the predictive control is applied in the harmonic model to suppress undesired harmonic currents to zero quickly. To decompose the voltage inputs and state variables into the fundamental and harmonic components, the fourth order band pass filter (BPF) is designed in the discrete-time domain for a digital implementation. For experimental verification, 2kVA prototype of a grid-connected inverter has been constructed using digital signal processor (DSP) TMS320F28335. The effectiveness of the proposed strategy is demonstrated through comparative simulation and experimental results.