• Journal of Power Electronics
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• v.15 no.2
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• pp.419-430
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• 2015

Flux estimation is a significant foundation of high-performance control for DC-excited synchronous motor. For almost all flux estimators, such as the flux estimator based on phase locked loop (PLL), DC drift causes fluctuations in flux magnitude. Furthermore, significant dynamic error may be introduced at transient conditions. To overcome these problems, this paper proposes an improved flux estimator for the PLL-based algorithm. Filters based on the generalized integrator are used to avoid flux fluctuation problems caused by the DC drift at the back electromotive force. Programmable low-pass filters are employed to improve the dynamic performance of the flux estimator, and the cutoff frequency of the filter is determined by the dynamic factor. The algorithm is verified by a 960V/1.6MW industrial prototype. Simulation and experimental results show that the proposed estimator can estimate the flux more accurately than the PLL-based algorithm in a cycloconverter-fed DC-excited synchronous machine vector control system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.866-874
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• 2008

Motor frequency can be measured by a hall sensor. Among the many hall sensors, a linear type hall sensor is good at high accuracy frequency measuring problem. However, in general, this linear type hall sensor has DC offset which can vary along sensor's operating voltage change. Therefore, In motor frequency measurement problem using the linear hall sensor, it needs an estimator that can estimate frequency and DC offset simultaneously. In this paper, we propose the least mean square estimator to estimate motor frequency. To verify its performance, we compare the LMS estimator with a commercial analog tachometer. Experimental results shows the proposed LMS estimator works well in varying frequency and stationary DC offset.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.278-281
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• 2000

In this abstract a novel control scheme of voltage-source PWM rectifiers using only dc-side sensors is proposed. The phase currents are reconstructed from switching states of the rectifier and the dc output current. For effective current control the currents are estimated by a predictive state observer. Also both the phase angle and the magnitude of th source voltage are estimated by phase estimator and magnitude estimator respectively. The validity of the proposed ac sensorless technique is verified by experimental results.

• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.348-350
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• 2008

A link voltage adjustment converter employing load power estimator for notebook computer adaptor is proposed. It is consisted of the boost converter as a power factor correction stage and the LLC resonant converter as a DC/DC conversion stage with a newly introduced link voltage adjustment method employing load power estimator, which helps to reduce the transformer size and peak of output voltage ripple, maintaining high efficiency over all the load condition. Experimental results with 85W converter are given to verify the validity of the proposed circuit.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.432-439
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• 1999

Several methods of induction motor drives which used speed estimators instead of shaft encoders have been reported. However those speed sensorless systems with estimators employing stator voltates and currents usually deteriorates as the speed gets lower because it is difficult to calculate the accurate rotor flux under the influence of DC-offset and saturation of integrators. In this paper to calculate rotor flux at low speed the new rotor flux estimator which replaces integra-tors with two lag circuits is proposed. Simulation and experiment results confirm the validity of this control scheme.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1389-1399
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• 2013

A discrete controller is designed for low power dc-dc switched mode power supplies. The approach is based on time domain and the control loop continuously and concurrently tunes the compensator parameters to meet the converter specifications. A digital state feedback control combined with the load estimator provides a complete compensation, which further improves the dynamic performance of the closed loop system. Simulation of digitally controlled Buck converter is performed with MATLAB/Simulink. Experimental results are given to demonstrate the effectiveness of the controller using LabVIEW with a data acquisition card (model DAQ Pad - 6009).

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1126-1129
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• 2000

The equivalent transformation of a brushless DC motor into an separately exited DC motor has been possible with the vector control technique. Vector control is an effective technique for controlling variable speed drives of brushless DC motors. Conventional vector controllers, however, suffer from electrical machine parameter variations because these controllers depend on the parameters. This paper presents the vector control of brushless DC motor using a neural network. In the proposed method, a neural network is employed as on-line estimator of the nonlinear dynamic equations of brushless DC motor. The neural network based vector controller has the advantage of robustness against machine parameter variations as compared with conventional vector controller The simulation results using Matlab/Simulink verify the useful of the proposed method.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.339-341
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• 2006

This paper presents a new method on controller design of brushless dc motors. In such drives the current ripples are generated by motor inductance in stator windings and the back EMF. To suppress the current ripples the current controller is generally used. To minimize the size and the cost of the drives it is desirable to control motors without the current controller and the current sensing circuits. To estimate the motor current it is modeled by a neural network that is configured as an output-error dynamic system. The identified model is essentially a one step ahead prediction structure in which fast inputs and outputs are used to calculate the current output. Using the model, effective estimator to compensate the effects of disturbance has been designed. The effectiveness of the proposed current estimator is verified through experiments.