• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.8
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• pp.48-59
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• 2011

This paper presents a new gain scheduling speed controller of permanent magnet synchronous generators(PMSG) for MW-class direct-driven wind turbine systems. The proposed gain scheduling speed controller performs the speed tracking at more than one operating point, and the first-order torque observer estimates the turbine torque which is needed to precisely control the speed of PMSG. The proposed speed controller verifies that the PMSG can successfully follow the reference speed which is determined via the maximum power point tracking(MPPT) control and pitch control under turbulent wind conditions. The proposed speed control algorithm is simulated using Simulink and its performance is confirmed through comparison with the results by PI control method.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1086-1087
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• 2007

This paper presents a implementation of speed sensorless vector control algorithm of induction motor using MATLAB/SIMULINK. The proposed method utilize the combination of the voltage model based on stator equivalent model and the current model based on rotor equivalent model, which enables stable estimation of rotor flux. Estimated rotor speed, which is used to speed controller of induction motor, is based on estimated flux. The overall system consisted of speed controller with the most general PI controller, current controller, flux controller. Speed sensorless vector control algorithm is implemeted as block diagrams using MATLAB/SIMULINK. Realtime control is perform by dSPACE DS1104 control board and Real-Time-Interface(RTI).

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.767-770
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• 1996

A H$\_$.inf./ contro theory was applied to motor speed control of two-mass system to get controller which acts effectively with control object including uncertainties. The H$\_$.inf./ control problem was composed and solved. After that, numerical simulation were executed to confirm ability of the controller which compared with PI controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2557-2561
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• 2005

The PID controller design and choosing PID parameters according to system response are proposed in this paper. Here PID controller is employed to control DC motor speed and Matlab program is used for calculation and simulation. Choosing PID parameters are demonstrated by several contrast experiments and a way for setting PID parameters values is discussed.

• Journal of Power Electronics
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• v.15 no.5
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• pp.1274-1285
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• 2015

This paper deals with model reference adaptive system (MRAS) speed estimators based on a secondary flux for linear induction motors (LIMs). The operation of these estimators significantly depends on an adaptation mechanism. Fixed-gain PI controller is the most common adaptation mechanism that may fail to estimate the speed correctly in different conditions, such as variation in machine parameters and noisy environment. Two adaptation mechanisms are proposed to improve LIM drive system performance, particularly at very low speed. The first adaptation mechanism is based on fuzzy theory, and the second is obtained from an LIM mechanical model. Compared with a conventional PI controller, the proposed adaptation mechanisms have low sensitivity to both variations of machine parameters and noise. The optimum parameters of adaptation mechanisms are tuned using an offline method through chaotic optimization algorithm (COA) because no design criterion is given to provide these values. The efficiency of MRAS speed estimator is validated by both numerical simulation and real-time hardware-in-the-loop (HIL) implementations. Results indicate that the proposed adaptation mechanisms improve performance of MRAS speed estimator.

• 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.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.184-189
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• 2014

In this paper, a new design method of vibration suppression controller for multi-inertia (especially, 3-ineritia) resonance systems is proposed. The controller consists of a digital fuzzy controller for speed loop and a digital PI controller for current minor loop. The three scaling factor of the fuzzy controller and two PI controller gains are determined by Differential Evolution (DE). The DE is one of optimization techniques and a kind of evolutionary computation technique. In this paper, we have applied the DE/rand/1/bin strategy to design the optimal controller parameters. Comparing with the conventional design algorithm, the proposed method is able to shorten the time of the controller design to a large extent and to obtain accurate results. Finally, we confirmed the effectiveness of the proposal method by the computer simulations.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.587-588
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• 2010

The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. This controller is controlled speed using artificial intelligent PI(AIPI) controller. Also, this paper is proposed control of maximum torque per ampere(MTPA) of induction motor. The performance of the proposed induction motor drive with maximum torque control using AIPI controller is verified by analysis results at dynamic operation conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2625-2632
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• 2009

Recently, a speed control method of induction motor by vector control theory is applied to highly efficient industrial field. The speed sensors attached to motor are used for detection of rotating speed. In the case using speed sensor, the installation of cable for minimization of electric noise, weaken maintenance, increase of price are demerit. Therefore the study of speed sensorless vector control theory performed activity. The design of sensorless vector controller for induction motor using tabu search is studied. The proposed sensorless vector control for Induction Motor is composed of two parts. The first part is for optimizing the speed estimation with initial PI parameters. The second part is for optimizing the speed control with initial PI parameters using tabu search. Proposed tabu search is improved by neighbor solution creation using Triangular random distribution. In order to show the usefulness of the proposed method, we apply the proposed controller to the sensorless speed control of an actual AC induction Motor System. The performance of this approach is verified through simulation and the experiment.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.53-55
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• 2006

This paper presents self tuning PI controller of IPMSM drive using neural network. NNPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.