• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1130-1136
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• 2009

A new control algorithm for the yaw motion control of a unicycle robot has been proposed in this paper. With the increase of life quality, there are various transportation systems such as segway and unicycle robot which provide not only transportation but also amusement. In most of the unicycle robots share the same technology in that the directions of roll and pitch are controlled by the balance controllers, allowing the robots to maintain balance for a long period by continuously moving forward and backward. However, one disadvantage of this technology is that it cannot provide the capability to the robots to avoid obstacles in their path way. This research focuses to provide the yawing function to the unicycle robot and to control the yaw motion to avoid the obstacles as desired. For the control of yawing motion, the yaw angle is adjusted to the inertia generated by the velocity and torque of a yawing motor which is installed in the center axes of the unicycle robot to keep the lateral control simple. Through the real experiments, the effective and robustness of the yawing control algorithm has been demonstrated.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.713-718
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• 2003

The CONDENSATION (Conditional Density Propagation) algorithm has a robust tracking performance and suitability for real-time implementation. However, the CONDENSATION tracker has some difficulties with real-time implementation for multiple people tracking since it requires very complicated shape modeling and a large number of samples for precise tracking performance. Further, it shows a poor tracking performance in the case of close or partially occluded people. To overcome these difficulties, we present three improvements: First, we construct effective templates of people´s shapes using the SOM (Self-Organizing Map). Second, we take the discrete HMM (Hidden Markov Modeling) for an accurate dynamical model of the people´s shape transition. Third, we use the competition rule to separate close or partially occluded people effectively. Simulation results shows that the proposed CONDENSATION algorithm can achieve robust and real-time tracking in the image sequences of a crowd of people.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1141-1145
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• 2005

This paper proposes a robust tension control algorithm for the let-off and take-up system driven by servo motor which is robust to disturbance and tension variation by using SVR(Support Vector Regression). Quality of textile goods in fiber manufacturing process highly depends on control of let-off, take-up and tension which are essential for constant tension control of yarn and textile fabrics and correct length of them. The physical properties of textile fabrics are very sensitive to several factors(temperature, humidity, radius change of warp beam etc.) which result in tension change. Rapid development of fiber manufacture machine for higher productivity requires control system for let-off, take-up and tension for robustness to sharp tension-variation and quick response. The validity and the usefulness of the proposed algorithm are thoroughly verified through numerical simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.744-747
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• 2010

This paper presents a novel adaptive control method for DC-DC converters applied in PV generator systems. We derive an state-space average model of the converter system and then propose a adaptive control methodology to enhance transient response performance for time-varying PV systems. A well-knwon Lyapunov theory is utilized for constructing our control algorithm. Numerical simulation demonstrates reliability of our control methodology and its superiority by comparison to a traditional control strategy.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.109-114
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• 2009

An orthogonal frequency division multiplexing(OFDM) system is effective to bandwidth because of orthogonality of subcarriers and robust to multipath fading. However, if there is a frequency offset, we lose the orthogonality of subcarriers and that results in inter-carrier interference(ICI) which increases errors in the system. In this paper, we propose an algorithm that estimates the fine frequency offset using a correlation method in OFDM systems. This scheme compares two correlation values in different frequency offsets with opposite directions. From the difference between two correlation values we can derive a fine frequency offset estimation algorithm. Its performance is verified by computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.730-735
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• 2014

This paper introduces a GP (Genetic Programming) based robust technique for the prediction of a heavy rain newsflash. The nature of prediction for precipitation is very complex, irregular and highly fluctuating. Especially, the prediction of heavy precipitation is very difficult. Because not only it depends on various elements, such as location, season, time and geographical features, but also the case data is rare. In order to provide a robust model for precipitation prediction, a nonlinear and symbolic regression method using GP is suggested. The remaining part of the study is to evaluate the performance of prediction for a heavy rain newsflash using a GP based nonlinear regression technique in Korean regions. Analysis of the feature selection is executed and various fitness functions are proposed to improve performances. The KLAPS data of 2006-2010 is used for training and the data of 2011 is adopted for verification.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.847-858
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• 2001

This paper considers the control model identification and H(sub)$\infty$ controller design for a tandem cold mill (TCM). In order to improve the performance of the existing automatic gauge control (AGC) system based on the Taylor linearized model of the TCM, a new mathematical model that can complement the Taylor linearized model is constructed by using the N4SID algorithm based on subspace method and the least squares algorithm based on ARX model. It is shown that the identified model had dynamic characteristics of the TCM than the existing Taylor linearized model. The H(sub)$\infty$ controller is designed to have robust stability to the system parameters variation, disturbance attenuation and robust tracking capability to the set-up value of strip thickness. The H(sub)$\infty$ servo problem is formulated and it is solved by using LMI (linear matrix inequality) techniques. Simulation results demonstrate the usefulness and applicability of the proposed H(sub)$\infty$ controller.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.2
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• pp.177-184
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• 2013

This paper proposes an enhanced Simultaneous Localization and Mapping (SLAM) algorithm based on matching laser image and Extended Kalman Filter (EKF). In general, laser information is one of the most efficient data for localization of mobile robots and is more accurate than encoder data. For localization of a mobile robot, moving distance information of a robot is often obtained by encoders and distance information from the robot to landmarks is estimated by various sensors. Though encoder has high resolution, it is difficult to estimate current position of a robot precisely because of encoder error caused by slip and backlash of wheels. In this paper, the position and angle of the robot are estimated by comparing laser images obtained from laser scanner with high accuracy. In addition, Speeded Up Robust Features (SURF) is used for extracting feature points at previous laser image and current laser image by comparing feature points. As a result, the moving distance and heading angle are obtained based on information of available points. The experimental results using the proposed laser slam algorithm show effectiveness for the SLAM of robot.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.6
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• pp.28-36
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• 2001

A robust adaptive sliding mode robot control algorithm is derived, which consists of a feed-forward compensation part and discontinuous control part. The unknown parameters is categorized into two groups, with group containing the parameters estimated on-line, and group containing the parameters not estimated on-line. Then a sliding control term is incorporated into the torque input in order to account for the effects of uncertainties on the parameters not estimated on-line and of disturbances. Moreover, the algorithm is computationally simple, due to an effective exploitation of the structure of manipulator dynamics. It is shown that, despite the existence of the parameter uncertainty and external disturbances, the controller is globally asymptotically stable and guarantees zero tracking errors.