• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.46-48
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• 2004

Recently, the study of sensorless drive of IPMSM is coming to be active. In sensorless drive, because the wrong estimation of the initial rotor position brings about the decrease of the starting torque, or a temporary reverse revolution, it is important to know the exact importation of the initial rotor position. In this paper, the initial rotor position estimation method is based on the current peak measured by applying the pulsewise voltage and the current peak is changed according to the rotor position owing to the saliency of the rotor. The effectiveness of the proposed algorithm is verified by the experimental results.

• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.127-131
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• 2003

This paper describes an initial pole position estimation method of a magnetic pole sensorless permanent magnet synchronous motor(PMSM) with an incremental encoder, The accurate initial pole position is estimated by using an efficient numerical method of Secant Method, which finds either of two zero torque/force positions and then the correct d-axis. It can be simply applicable to both rotary and linear PMSM because it only requires the tuned current controller and the relative position information. The experimental results show the validity of the proposed method with respect to highly accurate pole position estimation under the moderate moving distance and convergence time.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.578-580
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• 2005

This paper proposes the algorithm for the initial pole-position estimation of a surface PM-LSM, which is carried out under the pseudo-position control with-out a pole sensor and is insensitive to the motor parameters. This algorithm is based on the principle that the initial pole-position is calculated by the reverse trigonometric-function using the two reference currents, which are informed from the speed controller. The effectiveness of the proposed algorithm is confirmed by the arithmetical analysis and the experiment. IPP is well estimated within a satisfied moving-distance and a shorter estimation taken-time even if large disturbance such as cogging and friction are existed.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.1
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• pp.13-20
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• 2005

This paper has proposed an algorithm for the initial pole position estimation of a permanent magnet linear synchronous motor(PMLSM). The algorithm finds the initial pole position observing the maximum values of a position generated by the new proposed two reference frames for the same force input. So, the proposed algorithm does not utilize the motor parameters and is insensitive to them. Moreover, the proposed algorithm is easily realized because the proposed method is just using PI controller

• Journal of Power Electronics
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• v.6 no.2
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• pp.139-145
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• 2006

This paper describes the ultra precise position estimation of a servomotor using a sinusoidal encoder based on Arcsine Interpolation Method for the cost reduction of circuit design. The amplitude and offset errors of the sinusoidal encoder output signals, from the encoder itself and analog signal processing procedures, are effectively compensated and on-line tuned by utilizing a low cost programmable differential amplifier without any special expensive equipment. For a theoretical evaluation of the practical resolution of this system, the relationship between the amplitude of ADC(Analog to Digital Converter) input signal errors and the anticipated resolution is also addressed. The performance of the proposed method is verified by comparing it with speed control characteristics of the servomotor driving system using a digital incremental 50,000ppr encoder in the experiments.

• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.232-237
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• 2023

This paper presents a system for estimating the position of a magnet using a magnetic sensor. An algorithm is presented to analyze the waveform and output voltage values of the magnetic field generated at each position when the magnet moves and to estimate the position of the magnet based on the analyzed data. Here, the magnet is sufficiently small to be inserted into a blood vessel and has a micro-magnetic field of hundreds of nanoteslas owing to the small size and shape of the guide wire. In this study, a highly sensitive magneto-impedance (MI) sensor was used to detect these micro-magnetic fields. Nine MI sensors were arranged in a 3×3 configuration to detect a magnetic field that changes according to the position of the magnet through the MI sensor, and the voltage value output was polynomially regressed to specify a position value for each voltage value. The accuracy was confirmed by comparing the actual position value with the estimated position value by expanding it from a 1D straight line to a 3D space. Additionally, we could estimate the position of the magnet within a 3% error.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.716-722
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• 2016

Coordinate estimation is an essential function for autonomous navigation of a mobile robot. The optical mouse sensor is convenient and cost-effective for the coordinate estimation problem. It is possible to overcome the position estimation error caused by the slip and the model mismatch of robot's motion equation using the optical mouse sensor. One of the simple methods for the position estimation using the optical mouse sensor is integration of the velocity data from the sensor with time. However, the unavoidable noise in the sensor data may deteriorate the position estimation in case of the simple integration method. In general, a mobile robot has ready-to-use motion information from the encoder sensors of driving motors. By combining the velocity data from the optical mouse sensor and the motion information of a mobile robot, it is possible to improve the coordinate estimation performance. In this paper, a coordinate estimation algorithm for an autonomous mobile robot is presented based on the well-known Kalman filter that is useful to combine the different types of sensors. Computer simulation results show the performance of the proposed localization algorithm for several types of trajectories in comparison with the simple integration method.

• Proceedings of the KIPE Conference
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• 2011.11a
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• pp.279-280
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• 2011

In order to convert the mechanical movement of a linear generator to electrical power, the amateur current of the generator is controlled in accordance to the mover position. A linear encoder, usually used for direct detection of the mover position, not only is vulnerable to mechanical vibration, but also imposes significant constraint on the mechanical design of the generator system. Thus, this study proposes a method for indirect estimation of the mover position with emfs induced in amateur coils. The estimation algorithm is validated with simulation study.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.6
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• pp.602-609
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• 2011

This paper proposes a simple initial rotor position estimation method to obtain a stable startup performance for back EMF-based sensorless control. The proposed estimation method is achieved at standstill by using the current response to difference between each of the stator winding inductance. This initial rotor position estimation method can be easily implemented to control algorithm without any other external devices. The proposed algorithm is also not affected by motor parameter. The validity of the proposed method is demonstrated by experimental result.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.7
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• pp.9-17
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• 2000

Determining the position and velocity of mobiles is an important issue for efficient handoff and channel allocation in microcell structure. Our early work proposes a technique for estimating the mobile location in the microcellular architecture. This process is based on the three step position estimation which determines the mobile position by gradually reducing the area of the mobile position. Using three step method, the estimator first estimates the locating sector in the sector estimation step, then estimates the locating zone in the zone estimation step, and then finally estimates the locating block in the block estimate step. But this scheme is prone to errors when the mobile is located in the boundary of sectors or tracks. In this paper we propose the enhanced scheme to reduce the estimation error.