• Journal of Power Electronics
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• v.15 no.6
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• pp.1567-1576
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• 2015

Offline inductance identification of a permanent magnet synchronous motor (PMSM) is essential for the design of the closed-loop controller and position observer in sensorless vector controlled drives. On the base of the offline inductance identification method combining direct current (DC) offset and high frequency (HF) voltage injection which is fulfilled at standstill, this paper investigates the inverter nonlinearity effects on the inductance identification while considering harmonics in the induced HF current. The negative effects on d-q axis inductance identifications using HF signal injection are analyzed after self-learning of the inverter nonlinearity characteristics. Then, both the voltage error and the harmonic current can be described. In addition, different cases of voltage error distribution with different injection conditions are classified. The effects of inverter nonlinearities on the offline inductance identification using HF injection are validated on a 2.2 kW interior PMSM drive.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.9
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• pp.369-376
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• 2017

Recently, an RSSI-based fingerprinting localization technology has been widely used in indoor location-based services. In the conventional fingerprinting method, as many APs as possible are used to increase the accuracy of location estimation. In another study, a part of APs having the strongest RSSI signal intensity are selected and used to reduce the time spent for positioning. However, it does not reflect the influence of RSSI occurred from the changes of the surrounding environments such as human movement or moving obstacles in a real environment. The environmental changes may cause the difference between the predicted RSSI signal strength value and the measured value, and thus occur an unpredictable error in the position estimation. Therefore, in order to mitigate the error caused by environmental factors, it is necessary to select APs suitable for indoor positioning estimation considering the changes in the surrounding environments. In this paper, we propose a method to select stable APs considering the influence of surrounding environments and derive a suitable positioning algorithm. In addition, we compare and analyze the performance of the proposed method with that of the existing AP selection methods through experiments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.98-99
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• 2007

It is necessary to use satellite radio navigation system as well as satellite radio navigation augmentation system such as differential Global Positioning System to achieve the positioning accuracy and reliability requested by International Maritime Organization in port and coastal area. Especially, position accuracy of DGPS user is effected by accuracy of pseudorange correction broadcasted from DGPS reference station. This paper shows pseudorange correction calculation algorithm adopting a non-common error estimation filter in order to improve accuracy of pseudorange correction. Finally, this paper verifies that the pseudorange correction calculated by adopting a non-common error estimation filter satisfies performance specifications of RTCM.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.4
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• pp.71-80
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• 2006

Strapdown Inertial navigation systems consist of an inertial sensor assembly(ISA), electronic modules to process sensor data, and a navigation computer to calculate attitude, velocity and position. In the ISA, most gryoscopes such as RLGs and FOGs, have digital output, but typical accelerometers use current as an analog output. For a high precision inertial navigation system, sufficient stability and resolution of the accelerometer board converting the analog accelerometer output into digital data needs to be guaranteed. To achieve this precision, the asymmetric error and A/D reset scale error of the accelerometer board must be properly compensated. If the relation between the acceleration error and the errors of boards are exactly known, the compensation and estimation techniques for the errors may be well developed. However, the A/D Reset scale error consists of a pulse-train type term with a period inversely proportional to an input acceleration additional to a proportional term, which makes it difficult to estimate. In this paper, the effects on the acceleration output for auto-pilot situations and the effects of A/D reset scale errors during horizontal alignment are qualitatively analyzed. The result can be applied to the development of the real-time compensation technique for A/D reset scale error and the derivation of the design parameters for accelerometer board.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.3
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• pp.238-245
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• 2012

This paper presents a sensorless speed control of a 2-phase switch reluctance motor(SRM). The proposed sensorless control scheme is based on the slide mode observer with parameter compensator to improve the estimation performance. In the stand still position, the initial rotor position is determined by pulse current responses of each phase windings and the current difference. In order to determine an accurate initial rotor position, the two initial rotor positions are estimated by the difference of the pulse currents. From the stand still to the operating region, a simple open loop control which determines the commutation sequence by the pulse current of the unexcited phase winding is used. When the motor speed is reached to the sensorless control region, the estimated rotor position and speed by the slide mode observer are used to control the SRM. The flux calculator used in the slide mode observer is designed by phase voltage and the voltage drops in the phase resistance of the winding. The accuracy of the flux calculator is dependent on the phase resistance. For the continuous update of the phase resistance, current gradient at the inductance break point is used in this paper. The error of the estimated rotor position at the current gradient position is used to update the phase resistance to improve the sensorless scheme. The proposed sensorless speed control scheme is verified with a practical compressor used in home appliances. And the results show the effectiveness of the proposed control scheme.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.79-88
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• 2004

Gaze detection is to locate the position on a monitor screen where a user is looking by computer vision. Gaze detection systems have numerous fields of application. They are applicable to the man-machine interface for helping the handicapped to use computers and the view control in three dimensional simulation programs. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye's movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.8 cm of RMS error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.8-15
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• 2019

The PM synchronous motor drives with vector control have been applied to wide fields of industry applications due to its high efficiency. The rotor position information for vector control of a PM synchronous motor is detected from the rotor position sensors or rotor position estimators. The sensorless control based on the mathematical model of PM synchronous motor is generally used and it can be classified into back EMF -based sensorless control and magnet flux-based sensorless control. The rotor position estimating performance of the back EMF-based sensorless control is deteriorated at low speeds since the magnitude of back EMF is proportional to the motor speed. The magnitude of the magnet flux for estimating rotor position in the flux-based sensorless control is independent on the motor speed so that the estimating performance is excellent for wide speed ranges. However, the estimation performance of the model-based sensorless control may be influenced by the motor parameter variation since the rotor position estimator uses the mathematical model of the PM synchronous motor. In this paper, the rotor position estimation performance for the back EMF based- and flux-based sensorless controls is analyzed theoretically and is compared through the simulation and experiment when the motor parameters including stator resistance and inductance are varied.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.438-444
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• 2004

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Since the equations are based or the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied for this method. its performance is verified by the computer simulation and the experiment.

• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.846-855
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• 2020

A loose part monitoring system is used to detect unexpected loose parts in a reactor coolant system in a nuclear power plant. It is still necessary to develop a new methodology for the localization and mass estimation of loose parts owing to the high estimation error of conventional methods. In addition, model-based diagnostics recently emphasized the importance of a model describing the behavior of a mechanical system or component. The purpose of this study is to propose a new localization and mass-estimation method based on finite element analysis (FEA) and optimization technique. First, an FEA model to simulate the propagation behavior of the bending wave generated by a metal sphere impact is validated by performing an impact test and a corresponding FEA and optimization for a downsized steam-generator structure. Second, a novel methodology based on FEA and optimization technique was proposed to estimate the impact location and mass of a loose part at the same time. The usefulness of the methodology was then validated through a series of FEAs and some blind tests. A new feature vector, the cross-correlation function, was also proposed to predict the impact location and mass of a loose part, and its usefulness was then validated. It is expected that the proposed methodology can be utilized in model-based diagnostics for the estimation of impact parameters such as the mass, velocity, and impact location of a loose part. In addition, the FEA-based model can be used to optimize the sensor position to improve the collected data quality in the site of nuclear power plants.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.265-274
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• 2012

In this paper, we propose a method for preceding vehicle detection and tracking with motion estimation by radar-vision sensor fusion. The motion estimation proposed results in not only correction of inaccurate lateral position error observed on a radar target, but also adaptive detection and tracking of a preceding vehicle by compensating the changes in the geometric relation between the ego-vehicle and the ground due to the driving. Furthermore, the feature-based motion estimation employed to lessen computational burden reduces the number of deployment of the vehicle validation procedure. Experimental results prove that the correction by the proposed motion estimation improves the performance of the vehicle detection and makes the tracking accurate with high temporal consistency under various road conditions.