• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.133-138
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• 2011

This paper proposes a simple but robust self-tuning fuzzy logic controller for the speed regulation of a dual star induction machine based on indirect field oriented control. For feed the two star of this machine, two voltage source inverters based on sinus-triangular pulse-width modulation techniques are introduced. The simulation results show the robustness and good performance of the proposed controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1070-1073
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• 1993

A Fuzzy Logic Controller for handing the swell/shrink problems of nuclear steam generators is designed, implemented and tested on the compact nuclear simulator at Korea Atomic Energy Research Institute. Its performance is found to be better than of the PI controller originally being used. In terms of the total variations for the control actions and for the flow error curve, the ones by the fuzzy controller are found to be less than one third of those by the PI controller.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.932-941
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• 2014

In this paper, a simulation model for 7-phase BLDC motor drives for an Autonomous Underwater Vehicles (AUV) is proposed. A 7-phase BLDC motor is designed and the electrical characteristics are analyzed using FEA program and the power electronics drives for the 7-phase BLDC motor are theoretically analyzed and the actual implementation has been accomplished using Matlab Simulink. PI controller and fuzzy controller are compared for verifying the validity of the proposed model and the informative results are described in detail. Especially A fuzzy controller is used to characterize 7-phase BLDC motor, drive systems under normal and fault operating conditions.

• Journal of Power Electronics
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• v.8 no.2
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• pp.141-147
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• 2008

This paper deals with a new and improved control technique for shunt active filters (AF) used for compensating unwanted harmonic currents injected in the mains due to nonlinear varying loads. This work is motivated by the need to find a permanent solution to the rigorous hit and trial method for evaluating system parameters in an indirect control of AF. A fuzzy pre-compensated PI (Proportional-Integral) controller is used to fuzzify the reference DC voltage of AF to the controller input so that the overshoots and undershoots in its DC link voltage are minimized and the settling time is improved. A three-phase diode rectifier with R-L (Resistive-Inductive) load is used as a non-linear load to study the effectiveness of the proposed controller of the AF. Robustness to filter parameter variations, insensitivity to controller parameter variations, and transient response has been taken as performance evaluation parameters. The results are shown through simulations in Matlab using power system block sets to demonstrate the capability of the proposed controller of the AF.

• Proceedings of the KIPE Conference
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• 2010.11a
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• pp.276-277
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• 2010

This paper describes the control of a utility-connected doublefed induction machine (DFIM) for wind power generation systems (WPGS). Real and reactive powers (PQ) at the stator side of DFIM are strictly controlled to supply the power to the grid without any problems. In this paper the control is realized using Fuzzy PI controller based on the stator-flux orientation control.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.97-101
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• 1997

In recent years, there have been a number of applications of fuzzy logic in fuzzy reasoning system. The main objective of these applications is to approximate a decision making using the fuzzy reasoning system. This paper designs a fuzzy reasoning model for the decision making of registration fee at a private school, implements it applying for linguistic variables and fuzzy rules, and evaluates the practical availability of the model. The system accepts fuzzy rules, the type of membership functions, the domain of fuzzy sets and hedge, and fuzzifies the linguistic variables to generates fuzzy sets. The fuzzy sets generated are combined to constructs a solution fuzzy set. Finally, the system defuzzifies the solution fuzzy set to calculate a scalar value which is used for decision making.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.346-349
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• 1994

In this paper, we implemented the variable spped controller of an induction motor using the self-tuning fuzzy control algorithms, which recently is invoking the remarkable interest. Also we preposed a self-tuning technique of scale factors which could easily design the fuzzy speed controller. Comparing with conventional PI speed controller, the performances of proposed fuzzy controller such as dynamic responses and its the robustness against load disturbance were substantially improved.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.418-420
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• 1989

Many complex industrial processes cannot be satisfactorily controlled using the results of modern control theory, mainly because their precise structure is unknown. However this is often balanced by a considerable amount of operator's heuristic knowledges for the process which is difficult to quantify and utilize. Fuzzy set theory is a relatively new concept which allows this qualitativeness to be expressed rigorously and therefore in this paper modified PI type fuzzy logic controller is introduced and its usefulness for control is assessed.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.379-383
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• 2003

Parallel type fuzzy controller is designed by using a hybrid connected type fuzzy-PID controller and a model reference fuzzy controller. The first controller, consists of a fuzzy-PI and a fuzzy-PD making a hybrid type fuzzy-PID controller, plays a role as firstly reaching stable responses and secondly overcoming disturbance in plants. The second controller, model reference fuzzy controller, plays a role as reaching faster responses than other controllers. We have confirmed that the controller produces rapid and stable responses and overcomes disturbance by using parallel type fuzzy controller in a DC motor application.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.