• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.1
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• pp.59-64
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• 2003

This paper presents a new rotor position estimation method for brushless DC motors. The estimation error of the rotor position clearly provokes the phase shift angle misaligned between the phase current and the back-EMF waveforms, which causes torque ripple in brushless DC motor drives. Such an estimation error can be reduced with the help of the proposed neutral-voltage-based estimation method, which is structured as a closed loop observer. A neutral voltage appearing during the normal mode of the inverter operation is found to be an observable and control table measure, which can be used for estimating an exact rotor position. This neutral voltage is obtained from the DC-link current, the switching logic, and the motor speed values. The proposed algorithm, which can be easily implemented by using a single DC-link current and the motor terminal voltage sensors, is verified by simulation and experiment results.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.12
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• pp.971-982
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• 1989

An integrating position estimation algorithm has been developed for the navigation system of a free-ranging AGV system. The navigation system focused in this research work consists of redundant wheel encoders for the relative position measurement and a vision sensor for the absolute position measurement. A maximum likelihood method and an extended Kalman filter are implemented for enhancing the performance of the position estimator. The maximum likelihood estimator processes noisy, redundant wheel encoder measurements and yields efficient estimates for the AGV motion between each sampling interval. The extended Kalman filter fuses inharmonious positional data from the deadreckoner and the vision sensor and computes the optimal position estimate. The simulation results show that the proposed position estimator solves a generalized estimation problem for locating the vehicle accurately in space.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.955-957
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• 2003

In this paper deal with Initial Pole Position Estimation for Interior Permanent Magnet Motor. Generally, Brushless motor is considered Initial Pole Position with absolute encoder or resolver, etc. In the motor, the flux from the magnets is large enough to saturate the stator iron, results in different inductance values along the pole position. Based upon the relationship between magnitude of inductance and the resultant magnetic filed, initial pole position is estimated at standstill without position sensors, especially, this paper provide the direction of the magnetization. Finally, analysis results are presented to confirm ability of initial pole position estimation.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.497-502
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• 2010

The accurate estimation of position and direction of the mobile robot is essential for preparing precise movement and works in the inner complex environment. In this paper, we propose a robust estimation method of location and direction using the velocity of mobile robot in the inner GPS environment. The estimation using the inner GPS with ultrasonic sensors have to consider with various acoustic noise and sensor errors. We design a robust estimation method using a membership function based on uncertainty of the obtained information and robot velocity. The simulation results of the proposed method show effectiveness in the contaminated environment with position errors.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1284-1289
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• 2014

In this Paper, outdoor position estimation system was implemented using GPS (Global Positioning System) and INS (Inertial Navigation System). GPS position information has lots of errors by interference from obstacles and weather, the surrounding environment. To reduce these errors, multiple GPS system is used. Also, the Discrete Wavelet Transforms was applied to INS data for compensation of its error. In this paper, position estimation of the mobile robot in the straight line is conducted by EKF (Extended Kalman Filter). However, curve running position estimation is less accurate than straight line due to phase change in rotation. The curve is recognized through the rate of change in heading angle and the position estimation precision of the initial curve was improved by UPF (Unscented Particle Filter). In the case of UPF, if the number of particle is so many that big memory gets size is needed and processing speed becomes late. So, it only used the position estimation in the initial curve. Thereafter, the position of mobile robot in curve is estimated through switching from UPF to EKF again. Through the experiments, we verify the superiority of the system and make a conclusion.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.7
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• pp.532-539
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• 2018

A position estimation technique is presented for a missile using high-resolution range profiles obtained by three wideband radars. Radar measures a target range using a reflected signal from the surface of a missile. However, it is difficult to obtain the range between the radar and the origin of the missile. For this reason, the interior angle between the moving missile and tracking radar is calculated, and a compensated range between surface of the missile and its origin is added to the tracking range of the radar. Therefore, position estimation of a missile can be achieved by using three total ranges from each radar to the origin of the missile. To verify the position estimation of the missile, electromagnetic numerical analysis software was used to prove the compensated range according to the flight position. Moreover, a wideband radar operating at 500-MHz bandwidth was applied, and its range profile was used for the position estimation of a missile.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2339-2345
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• 2011

This paper proposes a new multi-filtered inertial navigation system to estimate the attitude and position of moving objects. This system has two states, the one is attitude state and the other is position/velocity state. For compensating IMU sensor errors, each of the two states uses a different filter: the attitude state uses the EKF and the position state uses the UPF. The fast and precise characteristics of the EKF have been properly utilized for the attitude estimation, while superior dynamic characteristics of the UPF have been fully adopted for the position estimation. The combination of these two filters in an inertial navigation system improves the system performance to be faster and more accurate. Experimental results demonstrate the superiority of this approach comparing to the conventional ones.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.114-115
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• 2014

This paper proposes a new speed and position estimation method for PMSM(Permanent Magnet Synchronous Motor) using low-resolution hall-effect sensors. In general, there are a variety of sensors to estimate rotor position for PMSM such as resolvers, and encoders. Position detection using hall-effect sensors that detect the flux of the rotor for rotor position is excellent method in terms of cost and space, but has low-resolution. To overcome this problem, this paper proposes a new speed and position estimation observer. The performance of the observer has been verified by simulations carried out using Matlab/Simulink.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.2
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• pp.124-129
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• 2005

This paper presents an advanced method for an initial pole position estimation of a Permanent Magnet Linear Synchronous Motor(PMLSM) that has an accurate incremental encoder for servo applications but does not have Hall sensors as a magnetic pole sensor. By appropriately using the secant method as a numerical method the proposed algorithm finds either of two zero force positions and then the correct d-axis by applying a q-axis test current. It only requires the tuned current controller and the relative position information md so it can be simply applicable to a rotary PMSM. The experimental results show the validity of the proposed method, which has an excellent performance with respect to an accurate pole position estimation under the minimal moving distance(average of about 85㎛) during the estimation process.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.1
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• pp.45-51
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• 2005

This paper presents a comparison of rotor position estimation of a switched reluctance motor(SRM) with built-in search coils by three methods. The search coil EMFs are not generated in the SRM with built-in search coils at standstill. So an initial rotor position estimation method is needed. In this paper squared euclidean distance, fuzzy logic and neural network methods we proposed for the estimation of initial rotor position. The simulated results of the three methods are compared. The simulated result of the squared euclidean distance method, which has the best performance, is supported by the experimental result.