• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.3
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• pp.201-208
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• 2015

The effects of dead-time and offset error, which cause output current distortion in single-phase grid-connected inverters are investigated this paper. Offset error is typically generated by measuring phase current, including the voltage unbalance of analog devices and non-ideal characteristics in current measurement paths. Dead-time inevitably occurs during generation of the gate signal for controlling power semiconductor switches. Hence, the performance of the grid-connected inverter is significantly degraded because of the current ripples. The current and voltage, including ripple components on the synchronous reference frame and stationary reference frame, are analyzed in detail. An algorithm, which has the proportional resonant controller, is also proposed to reduce current ripple components in the synchronous PI current regulator. As a result, computational complexity of the proposed algorithm is greatly simplified, and the magnitude of the current ripples is significantly decreased. The simulation and experimental results are presented to verify the usefulness of the proposed current ripple reduction algorithm.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.210-213
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• 2001

This study presents an effective variable forgetting factor method based on fuzzy logic to suppress frequency droop in extended integral load frequency control. The performance of the extended integral control is greatly dependent on the decaying factor. For an optimal or near optimal performance, it is necessary that the decaying factor as well as the feedback gains should be changed very quickly in response to changes in the system dynamics. However, because of its time-varing characteristic, the optimal decaying factor is difficult to be selected analytically. By adopting fuzzy set theory, the decaying factor can be determined quickly to respond to the variation of the feedback signals. This study builds a fuzzy rule base with use of the change of frequency and its rate as inputs. The computer simulation has been conducted for the single machine system. The simulation results show that the proposed fuzzy 1o81c based controller yields more improved control performance than the conventional PI controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.05a
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• pp.440-444
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• 2008

The 7-phase BLDC motor is possible for higher efficiency per the unit area, high power and high speed due to the increasing number of phase. Also, it can be looking forward to reduce the current ripple at a point of commutation by the increasing number of phase. Thus, a study for applications of servo system, medical and military instruments is progressing about the BLDC motor is manufactured with multi-phase, currently. This paper is used the fuzzy logic control method for speed control of 7-phase BLDC motor and this is compared with the conventional PI controller using by simulation and experimental results for verification validity of the fuzzy logic controller in this system. The 7-phase BLDC motor and controller are modeled by PSIM6.0 software of PowerSim co. in simulation and we are experimented by the test board that is composed with TMS320VC33-150 DSP controller of Texas Instruments co. and FLEX EPF6016TC144-3 of ALTERA co.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.2
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• pp.135-141
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• 2012

PMSM(Permanent Magnet Synchronous Motor) has periodic torque ripple from the cogging torque and load conditions. This paper proposes the modified PID speed controller to reduce the speed ripple of the PMSM. The proposed modified PID controller uses a selective D(Differential) control term according to the speed error and the differential of the speed error. The proposed speed controller produces an additional torque reference such as torque compensator based on PI controller according to the speed error and the differential of the speed error, and it can reduce the vibration of the conventional D-control term with reduced speed ripple. Since the additional torque reference of the proposed speed controller is changed by the sign of the speed error and the differential of the speed error, a simple function to determine the sign of the error is used to produce the compensated torque. The proposed control scheme is verified by the computer simulation and the experiments.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.9
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• pp.997-1005
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• 1990

Integral Error and State Feedback (IESF) controller which incorporates state feedback as a modern control scheme and integral action as a classical control scheme has better performance than that of conventional PID controller in linear time invariant system. But the structure of the IESF controller requires all the state variables of the system and is applicable only to pole assignable linear time invariant systems without time delay. Many industrial processes have large time delay and it is impossible to directly apply IESF control scheme to those processes. In this paper, a new controller structure, Modified Integral Error and State Feedback (MIESF) has been suggested in order to effectively control processes having time delay and its performance has been analyzed and its effectiveness has also been confirmed. As the proposed controller uses output feedback scheme based on integral error and state feedback (IESF) method, it can be simply designed by pole assignment algorithm irrespective of the order of the process. The MIESF controller can follow setpoint changes without overshoot. It is robuster than conventional Smith-Predictor plus PI(D) controller in case of occurring time delay mismatch and extra parameter mismatches between the process and the model. It can enhance control performance by intentional time delay mismatch.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.606-608
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• 1997

In this paper, Neuro-Fuzzy Controller(NFC), a fuzzy system realized using a neural network, is to adopt for the multivariable system. In the multivariable system, the interactive effects between the variables should be taken into account. A simple compensator, using the steady-state information can be obtained for open-loop stable systems, is presented to cope with this problem. However, it should be supposed that the plant is unknown to the control system designer, but an estimate of the DC gain has been obtained by carrying out experiments on the plant. Also, if the variables are not combinated completely, it is difficult to design the controller. Therefore, we design a neuro-fuzzy controller which controls a multivariable system with only input output informations, and compare its performance with that of a PI controller. In the proposed controller, the construction of the membership functions and rule base, which is highly heuristic, can be achieved using a training process. This allows the combination of knowledge of human experts and evidence from input-output data.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.6
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• pp.457-464
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• 2016

This study proposes a bi-directional buck-boost converter controller design method for ESS using the MATLAB SISO tool. The conventional two-loop controller design is based on a continuous S-domain model that designs each controller independently. The demerit of the conventional method is that optimal performance is not easily achieved and extensive trials and errors are required because two-loop systems interact with one another. Using the MATLAB SISO tool based on the design method proposed in this work overcomes the disadvantages of the conventional method. In the proposed method, the SISO tool can select the location of the poles and zeroes of the open loop system, thereby facilitating the effective design of a high-performance controller. The design sequence is detailed systematically, and the performance of the method is verified with a computer simulation and 10 kW experimental system.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1093-1098
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• 2017

In this study, we designed the system that helps drivers check all information about parking space at the entrance and find out whether the places is available or not, because the system has 'Image recognition function' which can even recognize car number plates exactly. Besides, we place the webcam close to the car number plate, so that car number can be identified more quickly. Finally, since we set the webcam high, the system keeps us from parking wrong places by displaying on the screen.

• Proceedings of the KIEE Conference
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• 2009.04b
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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.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.92-99
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• 2016

An electro-hydraulic actuator (EHA) is widely used in industrial motion systems and the increasing bandwidth of EHA position control is important issue. The model-inverse feedforward controller is known to extend the bandwidth of system. When the system has non-minimum phase (NMP) zeros, direct model inversion makes system unstable. To overcome this problem, an approximate model-inverse method is used. A representative approximate model inversion method is zero phase error tracking control (ZPETC). However, if zeros locate right half plane of z-plane, the approximate inverse model amplifies the high-frequency response. In this paper, to solve the problem of ZPETC, an adaptive model-inverse control is proposed. The adaptive algorithm updates feedforward term in real-time. The effectiveness of the proposed adaptive model-inverse position control strategy is verified by comparison with typical proportional-integral (PI) control and feedforward control by experiments. As a result, the proposed adaptive controller extends the bandwidth of EHA position control.