• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.76-86
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• 2013

As the basic Kalman filter is limited to be used for indoor navigation, and particle filters incur serious computational overhead, especially in mobile devices, we propose an adaptive hybrid filter for WiFi-based indoor positioning systems. The hybrid filter utilizes the same prediction framework of the basic Kalman filter, and it adopts the notion of particle filters only using a small number of particles. Restricting the predicts of a moving object to a small number of particles on a way network and substituting a dynamic weighting scheme for Kalman gain are the key features of the filter. The adaptive hybrid filter showed significantly better accuracy than the basic Kalman filter did, and it showed greatly improved performance in processing time and slightly better accuracy compared with a particle filter.

• Journal of Navigation and Port Research
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• v.41 no.5
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• pp.269-276
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• 2017

"Tracking" here refers to the estimation of a moving object with some degree of accuracy where at least one measurement is given. The measurement, which is the sensor-obtained output, contains systemic errors and errors that are due to the surrounding environment. Tracking filters play the key role of the target-state estimation after the updating of the tracking system; therefore, the type of filter that is used for the conduction of the estimations is crucial in the determining of the reliability of the updated value, and this is especially true since the performances of different filters vary when they are subjected to different environmental and initial conditions. The purpose of this paper is the conduction of a comparison between the performances of the ${\alpha}-{\beta}-{\gamma}$ filter and the Kalman filter regarding an ARPA-system tracking module that is used on board high-dynamic warships. The comparison is based on the capability of each filter to reduce noise and maintain a stable response. The residual error is computed from the difference between the true and predicted positions and the true and estimated positions for the given sample. The results indicate that the tracking accuracy of the Kalman filter is higher compared with that of the optimal ${\alpha}-{\beta}-{\gamma}$ filter; however, the response of the optimal ${\alpha}-{\beta}-{\gamma}$ filter is more stable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1441-1461
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• 2017

Nowadays, Dynamic Adaptive Streaming over HTTP (DASH) has become very popular in streaming multimedia contents. In DASH, a client estimates current network bandwidth and then determines an appropriate video quality with bitrate matching the estimated bandwidth. Thus, estimating accurately the available bandwidth is a significant premise in the quality of video streaming, especially when network traffic fluctuates substantially. To cope with this challenge, researchers have presented various filters to estimate network bandwidth adaptively. However, experiment results show that current schemes either adapt slowly to network changes or adapt fast but are very sensitive to delay jitter and produce sharply changed estimation. This paper presents a novel bandwidth estimation scheme based on Moving Average Convergence Divergence (MACD). We applied an MACD indicator and its two thresholds to classifying network states into stable state and agile state, based on the network state different filters are applied to estimate network bandwidth. In the paper, we studied the performance of various MACD indicators and the threshold values on bandwidth estimation. Then we used a DASH proxy-based environment to compare the performance of the presented scheme with current well-known schemes. The simulation results illustrate that the MACD-based bandwidth estimation scheme performs superior to existing schemes both in the speed of adaptively to network changes and in stability in bandwidth estimation.

• Journal of Power Electronics
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• v.11 no.4
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• pp.583-590
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• 2011

Three-level NPC inverters have been put into practical use for years especially in high voltage high power grids. This paper researches three-level active power filters (APFs). In this paper a mathematical model in the d-q coordinates is presented for 3-phase 3-wire NPC APFs. The deadbeat control scheme is obtained by using state equations. Canceling the delay of one sampling period and providing the predictive value of the harmonic current is a key problem of the deadbeat control. Based on this deadbeat control, the predictive output current value is obtained by the state observer. The delay of one sampling period is remedied in this digital control system by the state observer. The predictive harmonic command current value is obtained by the repetitive predictor synchronously. The repetitive predictor can achieve a better prediction of the harmonic current with the same sampling frequency, thus improving the overall performance of the system. The experiment results indicate that the steady-state accuracy and the dynamic response are both satisfying when the proposed control scheme is implemented.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.353-354
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• 2014

An active vibration control technique of a time-varying cantilever beam is proposed in this study. A simple in-house coil sensor instead of expensive commercial sensors was used to measure the vibrational displacement of the beam. Active band pass filters and artificial neutral net works detect the frequencies, amplitudes, and phases of the main vibration mode. The time constants of the low pass filter representing the positive position feedback controller are updated in real-time, which generates the control voltage input to actuate the piezoelectric actuator and suppress the vibration. An experiment was successfully performed to verify the algorithm for a cantilever beam, which fundamental natural frequency arbitrarily varies between 9 Hz ~ 18 Hz. The present active vibration suppression technique can be applied to variety of structures which undergoes large variation of dynamic characteristics while operating.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.243-250
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• 2012

This paper proposes a 3D map-building algorithm using one LRF (Laser Range Finder) while a mobile robot is navigating on the slanted surface. There are several researches on 3D map buildings using the LRF. However most of them are performing the map building only on the flat surface. While a mobile robot is moving on the slanted surface, the view angle of LRF is dynamically changing, which makes it very difficult to build the 3D map using encoder data. To cope with this dynamic change of the view angle in build 3D map, IMU and balance filters are fused to correct the unstable encoder data in this research. Through the real navigation experiments, it is verified that the fusion of multiple sensors are properly performed to correct the slope angle of the slanted surface. The effectiveness of the balance filter are also checked through the hill climbing navigations.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.2
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• pp.131-138
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• 2007

In this paper, a novel nonlinear control method of the CVCF(constant voltage and constant frequency) output voltage for the three-phase PWM inverter with LC output filters is proposed. A nonlinear modeling including the output LC filters is linearized by feedback linearization theory, the controllers of which can be designed based on a linear control theory. It is applied to the DC/AC power conversion of the PWM inverter for stand-alone wind power generation system. It has been verified by the experimental results that the proposed control scheme gives high dynamic responses at load variation as well as a zero steady-state error.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.112-119
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• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.32-38
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• 2002

This paper describes a development of a portable physical activity monitoring system using two accelerometers to quantify physical activity. The system hardware consists of two piezoresistive accelerometers, amplifiers with gain of 30, lowpass filters with cut-off frequency of 15Hz, offset control circuits, one-chip microcontroller and flash memory card. In order to evaluate the performance of the system we acquired 3 channel data at 32 sample/sec from body-fixed accelerometers in chest and right upper leg. And then the acquired data were processed by MatLab on personal computer. We tried to distinguish not only fundamental actions which are steady-state activities such as standing, sitting, and lying but also dynamic activities with walking, up a stairway, down a stairway, and running. Five subjects participated the evaluation process which compare the video data with the measured data. As a result, the activity classification rate of 90.6% on average was obtained. Overall results showed that the steady-state activities could be classified from the low component of 3-axis acceleration signal and dynamic activities could be distinguished from frequency analysis using wavelet transform and FFT. Finally, we could find that this system can be applied to acquire and analyze the static and dynamic physical activity data.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.79-84
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• 2015

Voltage sags are considered the dominant disturbances affecting power quality. Dynamic voltage restorers(DVRs) are mainly used to protect sensitive loads from the electrical network voltage disturbances such as sags or swells and could be used to reduce harmonic distortion of ac voltages. The typical DVR topology essentially contains a PWM inverter with LC Filter, an injection transformer connected between the ac voltage line and the sensitive load, and a DC energy storage device. For injecting series voltage, the PWM inverter is used and the passive filter consist of inductor(L) and capacitor(C) for harmonics elimination of the inverter. However there are voltage pulsation responses by the characteristic of the LC passive filter that eliminate the harmonics of the PWM output waveform of the inverter. Therefore, this paper presented design and feedback performance of LC filter used in the DVRs. The voltage control by LC filter should be connected in the line side since this feedback method allows a relatively faster dynamic response, enabling the elimination of voltage notches or spikes in the beginning and in the end of sags and strong load voltage THD reduction. Illustrative examples are also included.