• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.64-71
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• 2017

In this paper, Kalman filter and RRWA algorithm are used to estimate the accurate target in IR-UWB (Impulse-Radio Ultra Wideband) radar system, which enables accurate location recognition of indoors and outdoors with low cost and low power consumption. In the signal reflected by the target, unnecessary signals exist in addition to the target signal. We have tried to remove unnecessary signals and to derive accurate target signals and improve performance. The location of the targets is estimated in real time with one transmitting antenna and one receiving antenna. The Kalman filter was used to remove the background noise and the RRWA algorithm was used to remove the reflected signal. In this paper, we think that it will be useful to study the accurate distance estimation and tracking in future target estimation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.6-12
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• 2011

Electric vehicles and robots are real-time distributed control systems composed of multiple drive subsystems using micro controller units. Each control subsystem should be modular, compact, power saving, interoperable and fault tolerable in order to be incorporated into the networked real-time distributed control system. Under the networked real-time distributed control the synchronization problem can be occurred to the position and orientation tracking control due to the load variance, mismatch and time delay between the multiple drive subsystems. This paper suggests two types of position synchronization control of the single link manipulators. One of them is composed of cross controller, Kalman filter and disturbance observer, and the other uses the generation of target trajectories to minimize the gradient vector of the scalar function which is composed of the sum of square errors between the reference input vector and the output vectors. The availability of the proposed control schemes is shown through the control experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.698-707
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• 2017

This paper deals with predictive control methods of mobile robots for reference trajectory tracking control. Predictive control methods using predictive model are known as effective schemes that minimize the future errors between the reference trajectories and system states; however, the amount of real-time computation for the predictive control are huge so that their applications were limited to slow dynamic systems such as chemical processing plants. Lately with high computing power due to advanced computer technologies, the predictive control methods have been applied to fast systems such as mobile robots. These predictive controllers have some control parameters related to control performance. But these parameters have not been optimized. In this paper we employed the genetic algorithm to optimize the control parameters of the predictive controller for mobile robots. The improved performances of the proposed control method are demonstrated by the computer simulation studies.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.190-193
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• 2001

In order to verify the efficiency or availability and stability of photovoltaic(PV) generation systems, huge system apparatuses are needed, in general, in which an actual size of solar panel, a type of converter system and some amount of load facilities should be installed in a particular location. It is also hardly possible to compare a Maximum Power Point Tracking (MPPT) control scheme with others under the same weather and load conditions in an actual PV generation system. The only and a possible way to bring above-mentioned problem to be solved is to realize a transient simulation scheme for PV generation systems using real weather conditions such as insolation and surface temperature of solar cell. The authors, in this paper, introduces a novel simulation method, which is based on a real-time digital simulator (RTDS), for PV generation systems under the real weather conditions. Firstly, VI characteristic equation of a solar cell is developed as an empirical formula and reconstructed in the RTDS system, then the real data of weather conditions are interfaced to the analogue inputs of the RTDS. The outcomes of the simulation demonstrate the effectiveness of the proposed simulation scheme in this paper. The results shows that the cost effective verifying for the efficiency or availability and stability of PV generation systems and the comparison research of various control schemes like MPPT under the same real weather conditions are possible.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.9
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• pp.836-842
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• 2007

This paper describes the development of an automated operational orbit processing system (KGS automated Operational Orbit Processing System, KOOPS), which can determine, evaluate, update, and generate the orbit data automatically. Developed system can be applied to the multi satellite mission operations as a generic satellite orbit processing system in that the KOOPS has a capability to process various kinds of tracking data and assign pre and post processes according to the satellite system respectively. Results of applying the KOOPS to the KOMPSAT-1 and KOMPSAT-2 mission operations show that man power is greatly reduced and the efficiency and stability of the mission operations are significantly increased. The experiences to develop the KOOPS and operate multi satellite missions using this system can be applied to enhance the multi and generic flight dynamics system further.

• Journal of the Optical Society of Korea
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• v.20 no.4
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• pp.488-499
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• 2016

We present a design and optical simulation of a cost-effective hybrid daylighting/LED system composed of mixing sunlight and light-emitting diode (LED) illumination powered by renewable solar energy for indoor lighting. In this approach, the sunlight collected by the concentrator is split into visible and non-visible rays by a beam splitter. The proposed sunlight collector consists of a Fresnel lens array. The non-visible rays are absorbed by the solar photovoltaic devices to provide electrical power for the LEDs. The visible rays passing through the beam splitters are coupled to a stepped thickness waveguide (STW) by tilted mirrors and confined by total internal reflection (TIR). LEDs are integrated at the end of the STW to improve the lighting quality. LEDs’ light and sunlight are mixed in the waveguide and they are coupled into an optical fiber bundle for indoor illumination. An optical sensor and lighting control system are used to control the LED light flow to ensure that the total output flux for indoor lighting is a fixed value when the sunlight is inadequate. The daylighting capacity was modeled and simulated with a commercial ray tracing software (Lighttools^TM). Results show that the system can achieve 63.8% optical efficiency at geometrical concentration ratio of 630. A required accuracy of sun tracking system achieved more than ±0.5^o . Therefore, our results provide an important breakthrough for the commercialization of large scale optical fiber daylighting systems that are faced with challenges related to high costs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1224-1242
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• 2018

Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.81-87
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• 2016

This paper analysis the AM-SCS-MMA (Adaptive Modulus-Soft Constraint Satisfaction-MMA) based on the adaptive modulus and minimus-disturbance technique in order to improve the stability and robustness in low signal to noise power of current MMA adaptive equalization algorithm. In AM-SCS-MMA, it updates the filter coefficient applying the adaptive modulus and minimum-disturbance technique of deterministic optimization problem instead of LMS or gradient descend algorithm for obtain the minimize the cost function of adaptive equalization. It is possible to improve the equalizer filter stability, robustness to the various noise characteristic and simultaneous reducing the intersymbol interference due to the amplitude and phase distortion occurred at channel. The computer simulation were performed for confirming the improved performance of SCS-MMA. For these, the output signal constellation of equalizer, residual isi, MSE, EMSE (Excess MSE) which means the channel traking capability and SER which means the robustness were applied. As a result of computer simulation, the AM-SCS-MMA have slow convergence time and less residual quantities after steady state, more good robustness in the poor signal to noise ratio, but poor in channel tracking capabilities was confirmed than MMA.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1117-1128
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• 2015

In order to secure an important competitive advantage in manufacturing business, an automation and information system from manufacturing process has been introduced; however, small and medium enterprises have not met the power of information in the manufacturing fields. They have been managing the manufacturing process that is depending on the operator's experience and data written by hand, which has limits to reveal cause of defective goods clearly, in the case of happening of low-grade goods. In this study, we analyze critical factors which affect the quality of some manufacturing process in terms of 4M. We also studied the automobile parts processing of the small and medium manufacturing enterprises controlled with data written by hand so as to collect the data written by hand and to utilize sensor data in the future. Analysis results show that there is no deference in defective quantity in machines, while raw materials, production quality and task tracking have significant deference.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.38-48
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• 1996

We implemented and evaluated the preformance of a task level pipelined multicomputer "RV860-PIPE(Realtime Vision i860 system using PIPEline)" for computer vision applications. RV860-PIPE is a message-passing MIMD computer having ring interconnection network which is appropriate for vision processing. We designed the node computer of RV860-PIPE using a 64-bit microprocessor to have generality and high processing power for various vision algorithms. Furthermore, to reduce the communication overhead between node computers and between node computer and a frame grabber, we designed dedicated high speed communication channels between them. We showed the practical applicability of the implemented system by evaluting performances of various computer vision applications like edge detection, real-time moving object tracking, and real-time face recognition.