• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.3
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• pp.270-275
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• 2017

This paper proposes a double-phase-locked-loop (PLL) to improve the performance of position estimation in hall sensor-based permanent magnet synchronous motor control. In hall sensor-based control, a PLL is normally used to estimate the rotor position. The proposed Double-PLL consists of two PLLs, including a reset type integrator. The motor control is more accurate and has better performance than conventional PLL, such as a small estimated position ripple. The validity of the proposed algorithm is verified by simulations and experiments.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.316-320
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• 2004

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

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.35-40
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• 2015

This paper presents the sensorless position control of the Permanent Magnet Synchronous Motor (PMSM) using stator flux estimation and Phase Lock Loop (PLL). The field current and the torque current are required in order to perform the vector control of the PMSM. At this time, it is necessary for the torque to know the exact position of the magnetic flux generated by the permanent magnet, because the torque must be applied torque current in the direction orthogonal to the permanent magnet. In general the speed of the PMSM is controlled by using a magnetic position sensor. However, this paper, we estimates the stator flux by using the PLL method without the magnetic position sensor. This method is simple and easy, in addition it has the advantage of a stabile estimation of the rotor. Finally the proposed algorithm was confirmed by experimental results and showed the good performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.2
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• pp.169-176
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• 2012

GPS(Global Positioning System) is widely used for the position estimation of an aerial vehicle. However, GPS may not be available due to hostile jamming or strategic reasons. A vision-based position estimation method can be effective if GPS does not work properly. In mountainous areas without any man-made landmark, a horizon is a good feature for estimating the position of an aerial vehicle. In this paper, we present a new method to estimate the position of the aerial vehicle equipped with a forward-looking infrared camera. It is assumed that INS(Inertial Navigation System) provides the attitudes of an aerial vehicle and a camera. The horizon extracted from an infrared image is compared with horizon models generated from DEM(Digital Elevation Map). Because of a narrow field of view of the camera, two images with a different camera view are utilized to estimate a position. The algorithm is tested using real infrared images acquired on the ground. The experimental results show that the method can be used for estimating the position of an aerial vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.187-192
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• 1992

There are several potential error sources that can affect the estimation of the position of an object using combined vision and acceleration measurements. Two of the major sources, accelerometer dynamics and random noise in both sensor outputs, are considered. Using a second-order model, the errors introduced by the accelerometer dynamics are reduced by the smaller value of damping ratio and larger value of natural frequency. A Kalman filter approach was developed to minimize the influence of random errors on the position estimate. Experimental results for the end-point movement of a flexible beam confirmed the efficacy of the Kalman filter algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.403-403
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• 2000

Generally estimation of driving direction uses the way which uses lane detection and vanishing point in autonomous-driving system. Especially we use Sub-window for decreasing Process time when we detect lane, but fixed sub-window can not detect lane because of some factors in road image. So we suggest algorithm using one-dimension line scan method to detect an exact position of lane.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.503-504
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• 2015

This paper deals with the analysis of characteristics of position and speed estimator of an adaptive sensorless control algorithm for PMSM drives. The analysis shows that the back emf constant variation results in the position estimation error, but does not the speed estimation error. The simulation and experimental results are shown to verify the analysis result and the usefulness of the back emf constant estimator.

• 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 KIEE Conference
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• 2003.04a
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• pp.306-309
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• 2003

This paper presents a speed estimation algorithm of Switched Reluctance Motor(SRM) using flux-linkage modeling. The basic algorithm of this scheme is based on the flux linkage characteristic according to the phase current and the rotor position. A sufficient simulation and experimental data was used for neural network training. Through measurement of the phase flux linkage and phase currents, the neural network is able to estimate the rotor position and speed. The simulation result shows some good results, and possibility of this algorithm.

• Journal of Power Electronics
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• v.11 no.6
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• pp.856-863
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• 2011

In this paper a novel method of the Ant Colony Optimization algorithm for rotor position estimation in Switched Reluctance Motors is presented. The data provided by the initial assumptions is one of the important aspects used to solve the problems relative to an Ant Colony algorithm. Considering the nature of a real ant colony, it was found that the ants have no primary data for deducing which is the shortest path in their initial iteration. They also do not have the ability to see the food sources at a distance. According to this point of view, a novel method is presented in which the rotor pole position relative to the corresponding stator pole in a switched reluctance motor is estimated with high accuracy using the active and inactive phase parameters. This new method gives acceptable results such as a desirable convergence together with an optimized and stable response. To the best knowledge of the authors, such an analysis has not been carried out previously.