• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.115-117
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• 2008

Generally, because of the cost and the restricted manufacture standard, the motor control for home appliance have been used the method using hall sensors or the sensorless method. In the conventional sensorless method using home appliance, the resistor and the back-EMF coefficient are varied by the motor speed and the load torque. Therefore, these variations cause the position error when the sensorless control is operated. This paper proposes the compensation method for sensorless position error using 2-hall sensor pulse signals.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.121-130
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• 2000

A practical method is proposed to improve hit probability of the digital gun fire control system, when the measured rate of the tracking sensor becomes biased under some operational situation. For ground moving target it is shown that the well-known Kalman filter which uses position measurement only can be optimally used to eliminate the rate bias error. On the other hand, for 3D moving aircraft we present a new algorithm which incorporate FIR-type filter, which uses position and rate measurement at the same time, and the fixed-lag smoother using position measurement only, and show that it has the optimal performance in terms of both estimation accuracy and response time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.471-479
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• 2019

This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.509-515
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• 2006

This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System(SDINS) using electro-optical sensor. The proposed scheme uses the position or the attitude information from the sensor. For each case, Kalman filter model is derived and implemented. To show the effectiveness of the present compensation scheme, computer simulations have been carried out resulting in the boundedness of position and attitude errors.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.36-41
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• 2001

The performance of an inductive position sensor is described by the accuracy and the dynamic characteristics of the sensor. Both of these performance indices are affected by magnetic hysteresis and eddy currents. In this paper, a model of an inductive sensor is presented. This model includes the effects of hysteresis and eddy currents. Computer simulation shows that the sensitivity of the sensor is greatly affected by hysteresis and eddy currents. Repeability error increases with hysteresis and eddy currents effects. Results also show that eddy currents influence more on the sensor performance than hysteresis does. To reduce the effects of hysteresis and eddy currents, the sensor should be made out of thin laminations with high resistivity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.398-404
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• 2021

This paper proposes a method of using a magnetic position sensor to detect accurately the rotor position required to perform vector control of a permanent-magnet synchronous motor, particularly the initial rotor position at startup. In the existing vector control systems, the initial rotor position was determined using the output signals of the Hall sensors, or the control was performed in a sensorless method without using such a sensor. On the other hand, the accuracy is degraded due to the occurrence of a position detection error, and the practicality was not satisfactory. This paper attempts to detect the initial rotor position using a magnetic position sensor to solve this problem. This method is used to solve the deteriorating starting characteristics of the motor in the vector control system. In addition, to lower the price of a low-power vector control inverter, this paper proposes a method of integrating the existing sensors and reducing the price to less than half using a magnetic position sensor for speed and position detection.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.82-82
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• 2000

The way which estimates a position from Navigation is Dead-reckoning Navigation and Radio Navigation. Generally dead-reckoning navigation uses Gyro and odometer as sensor, but these have problems which are an integrating noise and a noise-sensitivity. Gps which is used by radio-navigation has a Troposthetic error and MultiPath ewer and so on. For minimizing a Troposthetic error and a Multipath error, this paper suggests to an algorithm which use vanishing point on CCD camera.

• 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.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.410-413
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• 1993

Chamferless peg-in-hole process of the cylindrical type parts using force/torque sensor and vision sensor is analyzed and simulated in this paper. Peg-in-hole process is classified to the normal mode (only position error) and tilted mode(position and orientation error). The tilted mode is sub-classified to the small and the big tilted mode according to the relative orientation error. Since the big tilted node happened very rare, most papers dealt with only the normal or the small tilted mode. But the most errors of the peg-in-hole process happened in the big tilted mode. This problem is analyzed and simulated in this paper using the force/torque sensor and vision senor. In the normal mode, fuzzy logic is introduced to combine the data of the force/torque sensor and vision sensor. Also the whole processing algorithms and simulations are presented.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1040-1047
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• 2011

This paper proposes a novel method based on error back propagation neural networks to fuse laser sensor data and ultrasonic sensor data for enhancing the accuracy of mapping. For navigation of single robot, the robot has to know its initial position and accurate environment information around it. However, due to the inherent properties of sensors, each sensor has its own advantages and drawbacks. In our system, the robot equipped with seven ultrasonic sensors and a laser sensor navigates to map two different corridor environments. The experimental results show the effectiveness of the heterogeneous sensor fusion using an error backpropagation algorithm for mapping.