• 전자공학회논문지SC
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• 제37권3호
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• pp.72-83
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• 2000

본 논문에서는 리칭모드 제어기와 신경 회로망을 이용하여 3상 유도전동기의 위치제어 시스템을 구현한다. 리칭모드 제어기는 위치오차와 속도오차의 궤적을 슬라이딩 평면으로 들어가도록 하고 신경회로망의 초기학습을 담당한다. 리칭모드 제어기의 구조는 슬라이딩 평면의 스위칭 함수로부터 간단히 구성하였다. 또한, 신경 회로망은 전향경로 신경망으로 구성되며 비선형 매핑능력과 탁월한 학습능력을 이용하여 유도전동기의 등가제어입력을 학습하도록 하였고 신경 회로망의 입력으로는 모터의 기준속도, 기준위치 및 엔코더를 이용하여 측정된 모터의 실제속도와 위치 등을 이용하였고 온라인 상태로 학습되도록 하였다. 이와 같이 복합적으로 구성된 제어기들을 유도전동기의 위치제어 시스템에 적용하였다. 본 논문에서 제안된 알고리즘의 타당성을 보이기 위해 기존의 PI 제어기와 비교평가를 하였으며 시뮬레이션과 실험결과로부터 초기운전 상태에서는 리칭모드 제어기가 주로 제어를 담당하지만 시간이 지남에 따라 신경회로망이 학습되어 신경 회로망이 주 제어기가 됨을 확인하였다. 아울러, 제안된 제어기가 PI 제어기보다 우수하고 특히 부하변동과 같은 외란에 강인함을 알 수 있었으며, 정상상태 오차가 현저히 감소하여 정밀한 제어가 가능함을 확인하였다.

• 전기전자학회논문지
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• 제24권3호
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• pp.877-882
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• 2020

본 논문에서는 계통연계형 인버터(Grid-connected inverter, GCI) 시스템을 위한 전류 제어 방법들의 성능 비교 연구를 제시한다. GCI 시스템을 위해 다양한 전류 제어 방법이 개발되었으며 각 제어기마다 장점과 한계를 가지고 있다. 본 논문에서는 GCI 전류 제어기들의 정상 상태 및 과도 상태에서의 동적 성능을 비교 분석한다. 제안한 전향보상기법(Command feedforward control, CFFC) 및 외란제거제어(Disturbance rejection control, DRC)가 모든 GCI 전류 제어기에 적용 전과 후의 성능을 비교 분석하였다. 제안된 CFFC와 DRC 제어 알고리즘을 주파수 영역에서 분석하고 성능 검증을 위해 각 GCI 전류 제어 방법들의 시뮬레이션 및 실험 모델을 개발하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.871-873
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• 1995

The purpose of this paper is to design and construct the compact type joint driver and controller of the biped robot. This biped robot will be designed to be suitable for the practical usages and applications in the work environment, which is not plat floor, like a stairs by taking the stand-alone style that equipped all the parts except power sources. Generally, highly nonlinear motion dynamics of the biped robot is realized to linear approximations by installing a high-ratio speed reducer at each joint and dividing motions into a several piecewise linear motions, which is realized by the digital controller design techniques. This biped robot has symmetrical structure to get the stable walking ability and also the hierachical structure to control each joint as well. That is, all of the joint controllers are connected to the main controller in the composition of overall controllers. The driver and controller of each joint uses PI controller that compensate the velocity and position errors by the data of the encoder. And the signal characteristics of each joint controller forms a trapezoid speed profile which is predefined by the values of direction, maximum velocity and position.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1146-1155
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• 2017

Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.32-34
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good Performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed model reference adaptive fuzzy control(MFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaption mechanism(FAM), MFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, MFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.576-588
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• 2014

The superiority of CMI (Cascaded Multilevel Inverter) is unparalleled in high power and high voltage STATCOM (Static Synchronous Compensator). However, the parameters and operating conditions of each individual power unit composing the cascaded STATCOM differ from unit to unit, causing unit voltage disequilibrium on the DC side. This phenomenon seriously impairs the operation performance of STATCOM, and thus maintaining the DC voltage balance and stability becomes critical for cascaded STATCOM. This paper analyzes the case of voltage disequilibrium, combines the operation characteristics of the cascaded STATCOM, and proposes a new DC voltage control scheme with the advantages of good control performance and stability. This hierarchical control method uses software to achieve the total active power control and also uses chopper controllers to enable that the imbalance power can flow among the capacitors in order to keep DC capacitor voltages balance. The operating principle of the chopper controllers is analyzed and the implementation is presented. The major advantages of the proposed control strategy are that the number of PI regulators has been decreased remarkably and accordingly the blindness of system design and debugging also reduces obviously. The simulation reveals that the proposed control scheme can achieve the satisfactory control goals.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 춘계학술대회 논문집
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• pp.404-407
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation even under ideal field oriented conditions. This paper is proposed adaptive fuzzy controller(AFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaptation mechanism(FAM), AFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, AFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• 전력전자학회논문지
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• 제27권3호
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• pp.192-199
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• 2022

In DC distribution systems, a TAB converter employing multiple transformers is one of the most widely used topologies due to its high power density, modularizability, and cost-effectiveness. However, the conventional control technique for a grid-connected mode in the TAB converter cannot maintain its reliability for an islanding mode under a blackout situation. In this paper, the islanding mode control technique is proposed to solve this issue. To verify the relative stability and dynamic characteristics of the control technique, small-signal models of both the grid connected and the islanding mode are derived. Based on the small-signal models, PI controllers are designed to provide suitable power control. The proposed control technique, the accuracy of small-signal models, and the performance of the controllers are verified by simulations and experiments with a 1-kW prototype TAB converter.

• 전기학회논문지
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• 제61권2호
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• pp.303-311
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• 2012

In this study, we introduce a dynamic process model as well as the design methodology of optimized fuzzy controller for its efficient application to vacuum production system to produce a semiconductor, solar module and display and so on. In a vacuum control field, PID control method is widely used from the viewpoint of simple structure and preferred performance. But, PID control method is very sensitive to the change of environment of control system as well as the change of control parameters. Therefore, it's difficult to get a preferred performance results from target system which has a complicated structure and lots of nonlinear factors. To solve such problem, we propose the design methodology of an optimized fuzzy PID controller through a following series of steps. First a dynamic characteristic of the target system is analyzed through a series of experiments. Second the process model is built up and its characteristic is compared with real process. Third, the optimized fuzzy PID controller is designed using genetic algorithms. Finally, the fuzzy controller is applied to target system and then its performance is compared with that of other conventional controllers(PID, PI, and Fuzzy PI controller). The performance of the proposed fuzzy controller is evaluated in terms of auto-tuned control parameters and output responses considered by ITAE index, overshoot, rise time and steady state time.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1535-1547
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• 2016

This paper proposes various design procedures for computing Power System Ancillary Service Requirement Assessment Indices (PSASRAI) for a Two-Area Thermal Reheat Interconnected Power System (TATRIPS) in a restructured environment. In an interconnected power system, a sudden load perturbation in any area causes the deviation of frequencies of all the areas and also in the tie-line powers. This has to be corrected to ensure the generation and distribution of electric power companies to ensure good quality. A simple Proportional and Integral (PI) controllers have wide usages in controlling the Load Frequency Control (LFC) problems. So the design of the PI controller gains for the restructured power system are obtained using Bacterial Foraging Optimization (BFO) algorithm. From the simulation results, the PSASRAI are calculated based on the settling time and peak over shoot concept of control input deviations of each area for different possible transactions. These Indices are useful for system operator to prepare the power system restoration plans. Moreover, the LFC loop coordinated with Redox Flow Batteries (RFB) has greatly improved the dynamic response and it reduces the control input requirements and to ensure improved PSASRAI, thereby improving the system reliability.