• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.9
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• pp.33-43
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• 2011

Since the fuzzy neural network(FNN) is universal approximators, the development of FNN control systems have also grown rapidly to deal with non-linearities and uncertainties. However, the major drawback of the existing FNNs is that their processor is limited to static problems due to their feedforward network structure. This paper proposes the recurrent FNN(RFNN) for high performance and robust control of SynRM. RFNN is applied to speed controller for SynRM drive and model reference adaptive fuzzy controller(MFC) that combine adaptive fuzzy learning controller(AFLC) and fuzzy logic control(FLC), is applied to current controller. Also, this paper proposes speed estimation algorithm using artificial neural network(ANN). The proposed method is analyzed and compared to conventional PI and FNN controller in various operating condition such as parameter variation, steady and transient states etc.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.1-5
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• 2004

This paper describe a control scheme for direct torque control of BLDC Motor. The proposed Luenberger Observer scheme calculate flux errors in order to control the torque and flux more correctly. This proposed control scheme has not the requirement of a separate current regulator and proportional-integral (PI) control of the flux and torque, there by improving transient performance and also has the advantage of less torque ripple in steady state with a fixed switching period. The effect of proposed method has been proven by simulations.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.11
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• pp.1759-1769
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• 1989

This paper presents the development of a simulator for an industrial robot. The simulator is characterized by a fully integrated dynamic model and a hardware oriented control scheme. The dynamic model includes the actuator dynamics as well as the manipulator dynamics to integrate the entire dynamics of the robot system. On the other hand, the control scheme is oriented as a hardware structure which is usually implemented in the industrial robot. That is to say, a conventional PI control law is used to regulate the position, the speed, and the current. A Pulse Wave Modulation (PWM)generator modulates the supplied voltage to the actuator. Since the simulator is consistent with the industrial robot system, it provides the essential design concepts for the development process of the robot. In practice, the simulator is applied to the SCARA robot which has been developed in GSIS. Here, it investigates the characteristics and performance of the robot with changing design parameters. Thus, the investigation furnishes criteria for the selection of acfuator, control gain, trajectory planning, etc.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.8
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• pp.68-74
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• 1998

The neural network predictiv econtroller (NNPC) is proposed for the attempt to mimic the function of brain that forecasts the future. It consists of two loops, one is for the prediction of output (NNP:neural network predictor) and the other one is for control the plant(NNC: neural network controller). The output of NNC makes the control input of plant, which is followed by the variation of both plant error and predictin error. The NNP forecasts the future output based upon the current control input and the estimated control output. The input and the output data of a system and a new method using evolution strategy are used to train the NNP. A two-step NNPC is applied to control the temeprature in boiler systems. It was compared with PI controller and auto-tuning PID controller. The computer simulaton and experimental results show that the proposed method has better performances than the other method.

• Journal of Power Electronics
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• v.8 no.2
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• pp.131-140
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• 2008

This paper presents a new control approach of DSTATCOM (distribution static compensator) for compensation of reactive power, unbalanced loading and harmonic currents under unbalanced non-sinusoidal ac mains. The control of DSTATCOM is achieved using Adaline based current estimator based on LMS algorithm to maintain source currents real and undistorted. The dc bus voltage of voltage source converter (VSC) working as DSTATCOM is maintained at constant voltage using a proportional-integral (PI) controller. The DSTATCOM system alongwith proposed control scheme is modeled in MATLAB to simulate the behavior of the system. The practical implementation of the DSTATCOM is carried out using dSPACE DS1104 R&D controller having TMS320F240 as a slave DSP. Simulated and implementation results are presented to demonstrate the effectiveness of the DSTATCOM with Adaline based control to meet the severe load perturbations with different types of loads (linear and non-linear) under distorted and unbalanced AC mains.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.487-492
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• 2000

This paper presents a novel method of slip-compensation for rotor time constant variation in indirect field orientation control of induction motor drives. In field oriented control due to variation of rotor time constant, decoupling between the flux and torque components of stator current is lost and hence, the performance of operation of the machine deteriorates. To solve the problem, the q-axis is aligned to reference frame without phase difference by comparing the real flux component with the reference flux component. Then to compensate the slip, PI controller is used. The proposed method keeps a constant slip by compensating the gain of direct slip frequency when the rotor resistance of induction motor varies. To prove the validations of the proposed algorithm in the paper, computer simulations and experiments are executed.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.51-57
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• 2017

Digital signage is becoming part of daily life across a wide range of visual advertisements segments market used in stations, hotels, retail stores, hotels, etc. The current digital signage system used in market is generally works on limited user interactivity with static contents. In this paper, a new approach is proposed using computer vision based dynamic audience adaptive cost-effective digital signage system. The proposed design uses the Camera attached Raspberry Pi Open source platform to employ the real-time audience interaction using computer vision algorithms to extract facial features of the audience. The real-time facial features are extracted using Haar Cascade algorithm which are used for audience gender specific rendering of dynamic digital signage content. The audience facial characterization using Haar Cascade is evaluated on the FERET database with 95% accuracy for gender classification. The proposed system, developed and evaluated with male and female audiences in real-life environments camera embedded raspberry pi with good level of accuracy.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.4_2
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• pp.491-499
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• 2021

Batteries are widely used for energy storage, such as ESS(Energy Storage System), electric vehicles, electric aircraft, and electric powered ships. Among them, a submarine uses a high power battery for an energy storage. When the battery of a submarine is discharged, a diesel generator generates AC power, and then AC/DC power converter change AC power to DC power for charging the battery. Therefore, in order to lower the current capacity of the diesel generator, it is necessary to use an AC/DC converter with a high input power factor. And, a power converter with a large power capacity must have high stability because it can lead to a major accident when a failure occurs. However, the control algorithm using the traditional PI controller is difficult to satisfy stability and dynamic characteristics. In this paper, we design the high power AC/DC converter with high input power factor for battery charging systems. And, we propose a stable control algorithm. The validity of the proposed method is verified through simulation and experiments.

• Journal of Magnetics
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• v.19 no.1
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• pp.90-100
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• 2014

Position estimation that uses only active phase voltage and current is presented, to perform high accuracy position sensorless control of a SRM drive. By extracting the amplitude of the first switching harmonic terms of phase voltage and current for a PWM period through Fast Fourier Transform (FFT), the flux-linkage and position are estimated without external hardware circuitry, such as a modulator and demodulator, which result in increased cost, as well as large position estimation error, produced when the motional back EMF is ignored near zero speed. A two-phase SRM drive system, consisting of an asymmetrical converter and a conventional closed-loop PI current controller, is utilized to validate the performance of the proposed position estimation scheme in comprehensive operating conditions. It is shown that the estimated values very closely track the actual values, in dynamic simulations and experiments.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.820-823
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• 2003

In this paper, we describe a design procedure for cascade controller for induction motor drives based on Genetic Algorithms(GAs). Most electric drives have two separate controllers for current and speed control, which are in general designed in two consecutive steps(firstly the current controller and then the speed controller). We search simultaneously for the couple of discrete anti-windup controllers achieving the optimal compromise of weighted cost and performance indices related to both current and speed responses.