• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1177-1179
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• 1999

This paper presents a design of artificial neural network power system stabilizer(ANNPSS) using adaptive evolutionary algorithm(AEA). We have proposed an adaptive evolutionary algorithm which uses both a genetic algorithm(GA) and an evolution strategy(ES), useing the merits of two different evolutionary computations. ANNPSS shows better control performances than conventional power system stabilizer(CPSS) in three-phase fault with heavy load which is used when tuning ANNPSS. To show the robustness of the proposed ANNPSS, it is applied to damp the low frequency oscillation caused by disturbances such as three-phase fault with normal and light load. the proposed ANNPSS shows better robustness than CPSS.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.917-922
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• 2008

In order to reduce energy consumption, secondary controlled system has been applied to many types of equipments. In lifting equipments or press machines using hydraulic cylinder, a hydraulic transformer is used as a control component instead of a valve for motion control and a component for recovering potential energy of load. The transformer is combination of a variable displacement pump/motor as a secondary controlled element and a fixed displacement pump/motor. Based on the nominal model derived from mathematical model, the feedback type two-degree-of-freedom controller is designed and implemented. From simulation results, the disturbances including nonlinear friction torque, leakage flow and load force can be compensated and good positioning accuracy is obtained. It show that the proposed controller is effective.

• Journal of Power Electronics
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• 제18권3호
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• pp.736-745
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• 2018

This paper presents an extended state observer (ESO) based direct torque control (DTC) for use in induction motor systems to handle the issues of time delays, load torque disturbances and parameter uncertainties. Direct torque control offers an excellent torque response and it does not require a proportion integration (PI) controller in the current loop. However, a PI controller is still adopted in the outer speed loop to generate the torque reference value, which is a slow method. An ESO based compound control scheme is proposed to improve the response rate and accuracy of the torque reference signal, especially when load torque is injected. In addition, the time delay problem is analyzed and compensated for in this paper to reduce torque ripples. The proposed disturbance compensation technique based direct control scheme is shown to have good performance both in the transient and stable states via simulations and experimental results.

• 한국정밀공학회지
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• 제17권7호
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• pp.106-112
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• 2000

The purpose of this paper is to study on the control of the engine idle speed under sudden A/C load which is one of the most severe disturbances on engines. Three types of the closed-loop controller are developed for the stable engine idle speed control. The input of the controller is an error of rpm. The output of the controller is an ISCV duty cycle. The anticipation delay is considered to deal with the delay time of the air mass in engine. The PID, Fuzzy and PID-type Fuzzy controllers with the anticipation delay have improved the engine idle speed condition more than current ECU map table under the A/C load.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권3호
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• pp.107-113
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• 2001

This paper deals with speed control of DC servo motor using a PID controller with a gain tuning based on a Back-Propagation(BP) Learning Algorithm. Conventionally a PID controller has been used in the industrial control. But a PID controller should produce suitable parameters for each system. Also, variables of the PID controller should be changed according to environments, disturbances and loads. In this paper described by a experiment that contained a method using a PID controller with a gain tuning based on a Back-Propagation(BP) Learning Algorithm, we developed speed characteristics of a DC servo motor on variable loads. The parameters of the controller are determined by neural network performed on on-line system after training the neural network on off-line system.

• 대한전기학회논문지
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• 제45권4호
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• pp.474-483
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• 1996

In this paper, as a part of the method improving stability, the load-flow calculation in D.C. power system and the models for stability analysis are studied with A.C-D.C. interconnected power systems transmission performed. Moreover, the theory is established in relation to each control method of D.C. power systems. Then the stability of A.C-D.C.interconnected power systems is compared and considered by the way of dividing the operating control method of the rectifier inverter converter into ACR-AVR, APR-A.gamma.R, A.alpha.R-ACR. The dynamics characteristic of terminal voltage, frequency, active-reactive power and rotor angle of the generator with disturbances and load fluctuations is considered. In addition, the characteristic of direct voltage, direct current, power and control systems. From this the comparative analysis of the direct current control method, the possibility of the stability analysis of A.C.-D.C. interconnected power system is considered. (author). refs., figs., tabs.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 춘계합동학술대회 논문집
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• pp.121-126
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• 2002

We proposed the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gains of input-output variables of fuzzy logic controller(FLC) and weights of neural network using Tabu search. Neural network was used for adaptively tuning the output gain of FLC. The weights of neural network was learned from the back propagation algorithm in real-time. To evaluate the usefulness of AFLC, we applied the proposed method to single-machine infinite system. AFLC showed the better control performance than PD controller and GAFLC[8] for. three-phase fault in nominal load which had used when tuning AFLC. To show the robustness of AFLC, we applied the proposed method to disturbances such as three-phase fault in heavy and light load. AFLC showed the better robustness than PD controller and GAFLC[8].

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.737-739
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• 1996

Abnormal conditions and disturbances in distribution system cause an immediate influence to the customers. Conventional detection schemes for the distribution abnormalities have been applied in limited extents mainly because of their low reliability. In this paper, we developed a disturbance identification system which monitors the load level after a transient, checks the harmonic behavior of the load, and finally makes decision on the cause of the disturbance. This system identifies and discriminates overcurrent faults, arcing ground faults, recloser activities, and foreign object or tree contacts. In the implementation of the identification system, we applied fuzzy logic to better represent some variables whose Quantities are expressed only in non-numerical terms.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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• pp.190-192
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• 2003

When generators trip on the occurrence of disturbance, the power system frequency declines by the amount of difference between demand and supply due to the imbalance between power generation and load. Even though the power system is operated with the same grid structure, generating capacity, and load, the resulting frequency decline and its recovery slope show different aspects according to the inertia constants of generators, spinning reserves, and the speed adjusting rates at the governors. From this point of view, we analysed differences of frequency decline at the various conditions in domestic power system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 B
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.