• The Transactions of the Korean Institute of Electrical Engineers B
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• v.52 no.10
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• pp.528-534
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• 2003

A grid connection algorithm is proposed for the doubly-fed induction generator (DFIG) which is widely adopted in high power variable speed wind turbine. Before the stator of DFIG is connected to grid, rotor-side converter is used to control the induced stator voltage. As a result, the stator transient current is limited below the rate value during the connection by the proposed synchronization of the stator voltage to the grid voltage. A wind power generation simulator using DC motor and wound-rotor induction generator is built and the dynamic characteristics of proposed algorithm is verified experimentally.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.163-165
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• 2006

This paper presents a implementation of speed sensorless vector control algorithm of induction motor using MATLAB/SIMULINK amd dSPACE DSl104 R&D board. The estimation of rotor flux linkage and rotor speed is carried out using model reference adaptive system(MRAS) method. Estimated rotor speed is used to speed controller of induction motor. Simulation results are presented to confirm speed sensorless vector control algorithm.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.51-52
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• 2010

In order to simplify the offline identification of induction motor parameters, a method based on optimization using a Tabu Search algorithm is proposed. The Tabu Search algorithm is used to minimize the error between the actual data and an estimated model. The robustness of the method is shown by identifying parameters of the induction motor in three different cases. The simulation results show that the method successfully estimates the motor parameters.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.744-746
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• 2000

This paper presents an optimum design of a linear induction motor(LIM) using genetic algorithm(GA). Sequential unconstrained minimization technique(SUMT) is used to transform the nonlinear optimization with constraints to a simple unconstrained problem. The objective functions of LIM such as trust, weight are optimized and the result was applied to the design of linear induction pump.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1035-1040
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• 1989

This paper describes first Boxes algorithm as a good method to generate the pulse patterns for a pulse width modulated inverter which has a good characteristics and simple to excute. Second we present the motor analysis fed by P.W.M. inverter in steady-state operation. In this analysis we improve the MRF ( Multiple Reference Frames ) to can be easy apply to analyse all the induction motor parameters. Finally we presented all the results obtained for a 3-phase induction motor.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1086-1091
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• 2005

This paper focuses on intelligent control of induction motor by hybrid system consisting of GA-PSO. Induction motor has been using in industrial area. However, it is challengeable on how we control effectively. From this point, an optimal solution using GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) is introduced to intelligent control. In this case, it is possible to obtain local solution because chromosomes or individuals which have only a close affinity can convergent. To improve an optimal learning solution of control, This paper deal with applying PSO and Euclidian data distance to mutation procedure on GA's differentiation. Through this approaches, we can have global and local optimal solution together, and the faster and the exact optimal solution without any local solution. Four test functions are used for proof of this suggested algorithm.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.85-91
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• 2000

This paper proposes a novel method with pseudo-on-line scheme using the optimized look-up table based on the genetic algorithm which does not use the gradient and finds the global optimum of an un-constraint optimization problem. The technique is a pseudo-on-line method that optimally estimates the parameters of fuzzy PID(FPID) controller for systems with non-linearity, using the genetic algorithm. The proposed controller(GFPID) with the auto-tuning function is applied to the on-line and real-time control of speed at 3-phase induction motor, and its computer simulation is carried out. simulation results show that the proposed methodis more excellent that conventional FPID and PID controllers.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.303-306
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• 1994

This paper presents a new rotor resistance identification algorithm for induction motors. The algorithm is derived form the fact that the slip frequency given in the d-q rotating frame is equal to that measured in the x-y fixed frame. Rotor resistance varies greatly with the machine temperature. In certain cases, the rotor resistance can increase 100 % over its ambient or nominal value. This deteriorates the dynamic performance of vector control systems for induction motors. However, the control scheme proposed in this paper is robust with respect to variations in rotor resistance because an efficient identification algorithm for rotor resistance is employed. To illuminate the performance of the proposed controller further, the simulation results are presented.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.11
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• pp.539-545
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• 2001

A simple analysis method for inverter-fed induction motor using F.E.M and harmonic equivalent circuit is proposed. And an optimum shape of rotor slot for 2Hp inverter-fed induction motor is determined by combining the proposed analysis method and an optimization algorithm. Conjugate gradient method is used for the optimization algorithm. The optimization is performed for higher efficiency and reduction of harmonic loss in the inverter-fed induction motor. The optimization results are verified by comparing with those of the time-step F.E.A.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.822-827
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• 2004

In this paper, an intelligent fault diagnosis system is proposed for induction motors through the combination of feature extraction, genetic algorithm (GA) and neural network (ANN) techniques. Features are extracted from motor vibration signals, while reducing data transfers and making on-line application available. GA is used to select most significant features from whole feature database and optimize the ANN structure parameter. Optimized ANN diagnoses the condition of induction motors online after trained by the selected features. The combination of advanced techniques reduces the learning time and increases the diagnosis accuracy. The efficiency of the proposed system is demonstrated through motor faults of electrical and mechanical origin on the induction motors. The results of the test indicate that the proposed system is promising for real time application.