• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.4
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• pp.39-47
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• 2000

This paper presents the sinusoidal tracking controller in error to eliminate the steady state control error and to improve the transient characteristics for input current in voltage source PWM converter with input current estimation. The estimation method of input current values and configuration of controller are described. DC output voltage is controlled by PI controller, and sinusoidal tracking current controller which tracks directly AC input current is used as input current controller. The sinusoidal tracking current controller can be used without any coordinate transformation algorithms.It is proved that the steady state deviation of input current reduces to zero and the proposed control system is not affected by input voltage from transfer functions of input current control system. The validity of proposed scheme is verified by simulations and experimental results for load resister and input voltage variation.

• Proceedings of the KIPE Conference
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• 2007.11a
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• pp.11-14
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• 2007

In recent years, installation of the new and renewable energy system is rapidly increasing. Because the new and renewable energy system is a practical distributed generation system to save energy resources and to keep environments clean. Conventional single-phase utility interactive inverter controls output current by using PI current controller. However, this method is insufficient to suppress harmonic current resulted from nonlinear loads in grid line. In this paper, in order to suppress periodic waveform distortion and improve THD(Total Harmonic Distortion), new type current controller added a parallel repetitive controller is proposed and then performance of the proposed controller was verified with computer simulation.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2656-2658
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• 1999

This paper presents a control scheme for a three-phase PWM converter system without any voltage sensors. Two input currents and one load current are measured. In a general PWM converter system, the required AC input and DC output voltage values in order to control the converter are estimated using the differential equations of the converter from the measured input currents and load current values in the switch modes of the converter circuit. The PI controller is used as DC voltage controller and sinusoidal tracking controller which tracks directly AC input current is used as input current controller. The Proposed method is verified by simulations. This paper describes the estimation method and configuration of the controller, and discusses steady state and transient performances of the converter

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.10
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• pp.59-68
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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 high performance control of induction motor drive using multi adaptive fuzzy controller. This controller has been performed for speed control with fuzzy adaptation mechanism (FAM)-PI, current control with model reference adaptive fuzzy control(MFC) and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM-PI, MFC and ANN controller. The performance of proposed controller is evaluated by analysis for various operating conditions using parameters of induction motor drive. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.177-177
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• 2000

In this paper, we propose a two-input two-output fuzzy controller to improve the performance of transient response and to eliminate the steady state error. The outputs of this controller are the control input calculated by position-type fuzzy controller and the accumulated error scaling factor. Here, the accumulated error scaling factor is adjusted on-line by fuzzy rules according to the current trend of the controlled process. To show the usefulness of the proposed controller, it is applied to several systems that are difficult to get satisfactory response by conventional PD controllers or PI controllers.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1380-1384
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• 2015

The DC motor has the strong characteristics in the speed response, the system parameter variations and the external influence and is used as the speed controller with its good starting torque in the distributing industry. However development of the Microprocessor which is for high speed switching program can make better control system. This paper introduce to design of the high-effective DC motor controller that is using Software Bang-Bang Program of Fuzzy algorithm and to verify a PI controller and a Fuzzy controller.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.93-101
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• 1993

The transfer function of vector-controlled induction motor is represented along with both unstructured and structured uncertainty such as the error of rotor time constant and current ripple. The low-pass-filter behavior of a magnetizing inductance gets rid of unstructured uncertainty in the transfer function. The robust controller to compensate variation of the transfer function is designed using simple P-I linear controllers. The coefficients of speed PI controller are determined from an overshoot and a rising time of system and the coefficients of model-following PI controller are obtained using the solution of Riccati equation of LQR control in the state space equation of the error system. Experimental results with the DSP-based model-following robust controller are shown a good robustness against the structured uncertainty of the motor.

• Proceedings of the KIPE Conference
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• 2009.11a
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• pp.206-208
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• 2009

In this paper, a systematical controller design method for a twostage grid-connected photovoltaic power conditioning system is proposed. For a pre-stage boost converter to achieve the stable operation in the entire region of solar array, the digital resistive current mode controller is used. This algorithm is very simple to implement with a digital controller and there is no power stage parameter dependency in the controller design. For a post-stage single-phase full-bridge inverter, a PI controller with a feedforward compensation for the inner current control is employed. Furthermore, in case that the operating point of the solar array under varying environmental conditions is higher than the required voltage for the inverter current control, the bypass mode for the boost converter is possible for the more efficient operation. The proposed control scheme is validated through the experiment of the prototype two-stage power conditioning system hardware with a 200W solar array.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.157-165
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• 2002

This paper presents the implementation of the speed control system for 3 phase induction motor using PD controller and neural networks. The PD controller is used to control the motor and to train neural networks at the first time. And neural networks are widely used as controllers because of a nonlinear mapping capability, we used feedforward neural networks(FNN) in order to simply design the speed control system of the 3 phase induction motor. Neural networks are tuned online using the speed reference, actual speed measured from an encoder and control input current to motor. PD controller and neural networks are applied to the speed control system for 3 phase induction motor, are compared with PI controller through computer simulation and experiment respectively. The results are illustrated that the output of the PD controller is decreased and feedforward neural networks act main controller, and the proposed hybrid controllers show better performance than the PI controller in abrupt load variation and the precise control is possible because the steady state error can be minimized by training neural networks.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.5
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• pp.466-476
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• 2013

This paper describes a fuzzy control method to control the output voltage of the three-phase Z-source PWM rectifier. A fuzzy control system is a control system based on fuzzy logic, and the fuzzy controller uses a single input fuzzy theory with its fuzzification. Analytical structure of the simplest fuzzy controller is derived through the triangular membership functions with its fuzzification. By setting the membership functions of the fuzzy rules, fuzzy control is achieved. The PI portion of the output DC voltage controller is controlled by fuzzy method. To confirm the validity of the proposed method, the simulation and experiment were performed, The simulation is performed with PSIM and MATLAB/SIMULINK. For the experiment, we used a DSP(TMS320F28335) controller to compute the reference value and generate the PWM pulses. For the transient state performance of the output DC voltage control of Z-source PWM rectifier, the PI controller and fuzzy controller were compared, also the conventional PWM rectifier and Z-source PWM rectifier were compared. From the results, the Z-source rectifier could allow to buck or boost of the output DC voltage. Through the analysis of the transient state, we could observe that the fuzzy controller has better performance than the conventional PI controller.