• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.371-375
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• 1998

This paper proposes a programmable low pass filter(LPF) to estimate stator flux for speed sensorless stator flux orientation control of induction motors. The programmable LPF is developed to solve the dc drift problem associated with a pure integrator and an analog LPF with fixed pole. of the programmable LPF is located far from the origin in order to decrease the time constant as speed increases. The programmable LPF has the phase and the magnitude compensator to exactly estimate stator flux in a wide speed range. So, the drift problem is much improved and the stator flux is exactly estimated in the wide speed range. The validity of the proposed programmable LPF is verified by speed sensorless vector control of a 2.2[kW] three-phase induction motor.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.409-412
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• 2001

When the vector control, which does not need a speed signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. In this paper, describes a rotor speed estimate method of induction motor based on the theory of counter EMF MRAS. This method eliminated the pure integrator. and we can be expected to rapid responsibility of the speed Identification. Therefore, we improve the initial condition of the integrator and drift problem. The stability of speed estimator is proved on the basis of hyperstability theory. In order to confirm the performance of the proposed system. Simulation and experiment is performed.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2057-2059
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• 2001

A nonlinear adaptive speed controller is designed for induction motors. Only the measurement of the stator current is used to design the controller and the observers. The sliding mode cascade observer is introduced to estimate the stator current and its time derivatives. The open-loop observer are designed to estimate the rotor flux and its time derivatives. The adaptive observer is also designed to estimate the rotor resistance. Sequentially, the rotor speed can be calculated using these estimated values. It is shown that the estimation errors of the corresponding states and the parameter converge to the specified residual set. It is also shown that the speed controller using these estimates is performed well. The experimental results are represented to investigate the validity of the proposed observer and controller.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.859-866
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• 2009

The article discusses an issue of estimating the airspeed of an autonomous flying vehicle. Airspeed is the difference between ground speed and wind speed. It is desirable to know any two among the three speeds for navigation, guidance and control of an autonomous vehicle. For example, ground speed and position are used to guide a vehicle to a target point and wind speed and airspeed are used to maximize flight performance such as a gliding range. However, the target vehicle has not an airspeed sensor but a ground speed sensor (GPS/INS). So airspeed or wind speed has to be estimated. Here, airspeed is to be estimated. A vehicle's dynamics and its dynamic parameters are used to estimate airspeed with attitude and angular speed measurements. Kalman filter is used for the estimation. There are also two major sources arousing a robust estimation problem; wind speed and altitude. Wind speed and direction depend on weather conditions. Altitude changes as a vehicle glides down to the ground. For one reference altitude, multiple model Kalman filters are pre-designed based on several reference airspeeds. We call this group of filters as a cluster. Filters of a cluster are activated simultaneously and probabilities are calculated for each filter. The probability indicates how much a filter matches with measurements. The final airspeed estimate is calculated by summing all estimates multiplied by probabilities. As a vehicle glides down to the ground, other clusters that have been designed based on other reference altitudes are activated. Some numerical simulations verify that the proposed method is effective to estimate airspeed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.561-564
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• 2004

This paper proposes a new application of Kalman filter to estimate speed sensorless DC motor. Kalman filter can estimate the system state variables accurately; even the system input is disturbed with noise. In the design, the mathematical model of DC motor in discrete state-space form will be created; the speed of DC motor which is considered as state variable and can be estimated by using Kalman filter. In the experiment; TMS320C31 floating point digital signal processor is used for hardware implementation, the input is disturbed with/and without white noise in the experiment. The experimental results show the speed of DC motor which is estimated by Kalman filter has good accuracy when compared with the results from tacho-meter.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.392-397
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• 1998

This paper proposes a programmable low pass filter(LPF) to estimate stator flux for speed sensorless stator flux orientation control of induction motors. The programmable LPF is developed to solve the dc drift problem associated with a pure integrator and a LPF with fixed pole. The pole of the programmable LPF is located far from the origin to decrease the time constant as speed increases. The programmable LPF has the phase and the magnitude compensator to exactly estimate stator flux in a wide speed range. So, the drift problem is much improved and the stator flux is exactly estimated in the wide speed range.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.721-729
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• 2009

Recently, there has been growing necessity to estimate the future travel demand of high speed train because the circumstance of high speed train service is rapidly changing with the launching of 2011 second stage of Gyeongbu high speed railway(Dongdaegu-Busan) and the completion of 2014 first stage of Honam high speed railway(Yongsan-Gwangju), etc. This study was designed to estimate future travel demand by analyzing the transport performance and train service characteristics of Gyeongbu and Honam line. This study presents the maximum load section and the changed future travel demand, which will be applied to establish a train operation plan.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.2
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• pp.101-109
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• 2005

The newly developed speed sensorless control scheme is proposed to estimate both motor speed and rotor resistance simultaneously using variable rotor flux. The rotor flux is given as sinusoidal waveform with an amplitude and a frequency without affecting precise torque control. Especially the proposed method makes the simultaneous estimation of rotor resistance and speed with high precision even though at the low speed area including a few rpm. Moreover, on-line identification of rotor resistance can be performed simply without calculating troublesome trigonometric functions and complicated integral computation. Therefore, the proposed system can be accomplished by using very cheap microprocessors for several applications. The results of the numerical simulations and experiments demonstrate that this method is effective to estimate the speed and on-line identification of rotor resistance for sensorless induction motors.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.726-728
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• 2004

In this paper, the gain of the observer is properly set up using the fuzzy control and Fuzzy-Sliding observer(FSQ) that have a superior transient characteristic and is easy to implement compared to the existing method is designed. It estimate the differentiation of the armature current directly using the armature current measured in the AC motor. It estimate the speed of the rotor using the differentiation. It is proposed speed sensorless control method using the estimated speed. Optimal gain of speed observer(Luenberger observer) was set up using the fuzzy control and adapted speed control of AC servo motor. To verify the performance of designed Fuzzy-Sliding observer, simulation compared with fixed speed observer gain of G.B Wang and S.S Peng's sliding observer is performed. Also, it was proved the excellence and feasibility of the proposed observer from the comparison test with a speed sensor and without a speed sensor which used a highly efficient drive and 400W AC servo motor starting system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.996-1003
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• 1999

This paper propose a position-speed controller with an estimator which can estimate states and disturbance. The overall control system consists of two parts: the position-speed controller and an estimator. The Kalman filter applied as state-feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear, unbiased and minimum error variance recursive algorithm to optimally estimate the unknown state. Therefore, we consider the error problem about the servo system modeling and the measurement noise as a stochastic system and implement a optimal state observer, and enhance the estimate performance of position and speed using that. Using two-degree-of freedom(TDOF) conception, we design the command input response and the closed loop characteristics independently. The servo system is to improve the closed loop characteristics without affecting the command imput response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer using a inverse-transfer matrix. Therefore, the performance of overall position-speed controller is enhanced. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real servo system.