• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.121-127
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• 2010

We consider the robust trajectory tracking control problem for a skid steering mobile robots. A dynamic model is derived accounting for the effects of wheel skidding. The control design utilizes the dynamic feedback linearization techniques, so as to obtain a predictable behavior for the instantaneous center of rotation thus preventing excessive skidding. The additive controller using the sliding mode type is then robustified against the unmodelled dynamics and parameter uncertainty. Simulation results show the good performances under excessively uncorrected estimations of the longitudinal forces and the lateral resistive forces caused by the skidding of the wheels in tracking trajectories.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.696-701
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• 2004

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion, have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• Journal of Mechanical Science and Technology
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• v.19 no.9
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• pp.1742-1752
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• 2005

This paper presents a Multiple Target Tracking (MTT) Adaptive Cruise Control (ACC) system which consists of three parts; a multi-model-based multi-target state estimator, a primary vehicular target determination algorithm, and a single-target adaptive cruise control algorithm. Three motion models, which are validated using simulated and experimental data, are adopted to distinguish large lateral motions from longitudinally excited motions. The improvement in the state estimation performance when using three models is verified in target tracking simulations. However, the performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. The MTT-ACC system is tested under lane changing situations to examine how much the system performance is improved when multiple models are incorporated. Simulation results show system response that is more realistic and reflective of actual human driving behavior.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.745-750
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• 2008

Uncertain dynamic parameters and joint flexibility have been problem to control robot manipulator precisely. Hence, even if the controller tracks the desired trajectory well with the feedback of the motor encoders, it is hard to achieve the desired behavior at the end-effector. In this paper, robot trajectory is taught by a general heuristic iterative learning control (ILC) algorithm in order to reduce tracking error of the tool center point (TCP) and the results of tracking with 6 DOF industrial robot manipulator are presented. The performance is verified based on ISO 9283.

• Journal of Power Electronics
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• v.12 no.2
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• pp.294-304
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• 2012

This paper proposes a fuzzy speed tracking controller and a fuzzy rotor angular acceleration observer for a surface-mounted permanent magnet synchronous motor (SPMSM) based on the Takagi-Sugeno (T-S) fuzzy model. The proposed observer-based controller is robust to load torque variations since it utilizes rotor angular acceleration information instead of the load torque value. Linear matrix inequality (LMI) sufficient conditions are given to compute the gain matrices of the speed tracking controller and the observer. In addition, it is mathematically verified that the proposed observer-based control system is asymptotically stable. Simulation and experimental results are presented to confirm that the proposed control algorithm assures a better transient behavior and less sensitivity under model parameter variations than the conventional PI control method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.2
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• pp.28-33
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• 2007

In this paper, we are studied on the direction and formation of carbonized conductive path according to surface leakage current between electrodes. The characteristics of the tracking as surface is broken down between exposed live parts. Using the HSIS(high speed imaging system. 100,000[fps], redlake ltd., USA), it took photographs by arc growth mechanism occurred in on/off surge, ground fault and discharge between electrodes. Then the results was analyzed. Hereafter, it expected effects that application of energy utility technology through the arc control.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.941-949
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• 2010

The present study investigated the swimming pattern and appendage postures of a copepod species, Calanus sinicus, which prevails in the south-east sea of the Korean peninsula, by employing a digital holographic particle tracking velocimetry(PTV) technique. The results showed that the copepod Calanus sinicus had various swimming patterns such as hover, hop, sink, cruise, and downward cruise. Most frequent pattern was the 'hop and sink'. The average swimming speeds ranged from 1.1 to 45.7 body-lengths/s, and the corresponding flow Reynolds number ranged from $10^0$ to $10^2$.

• Proceedings of the Korean Society of Rheology Conference
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• 2006.06a
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• pp.61-64
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• 2006

Soft materials, such as polymer solutions, gels and filamentous protein materials in cells, show complicated behavior due to their complex structures and dynamics with multiple characteristic time and length scales. Several complementary techniques have been developed to measure viscoelastic of soft materials. Especially, particle tracking microrheology, using the Brownian motion of particles in a medium to get rheological properties, has recently been improved both theoretically and experimentally. Compared to other conventional methods, video particle tracking microrheology has some advantages such as small sample volume, detecting spatial variation of local rheological properties, and less damage to sample materials. With these advantages, microrheology is more suitable to measure the properties of complex materials than other mechanical rheometries.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.5
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• pp.295-302
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• 2011

This paper proposes facial feature tracking based on modified ART2 neural networks. And we also suggest new measurement devices such as 'Persistence Exponent' and 'Moving Space Exponent' for the criterion of input vector which consists features. The proposed methods have been applied to classify 48 students by 2-class (ADHD positive, ADHD negative). The results of the experiment have shown that the proposed methods are effective for ADHD Behavior Pattern Classification based on the Image Processing.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.772-786
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• 2021

The process of tracking suspicious behavior manually on a system and gathering evidence are labor-intensive, variable, and experience-dependent. The system logs are the most important sources for evidences in this process. However, in the Microsoft Windows operating system, the action events are irregular and the log structure is difficult to audit. In this paper, we propose a model that overcomes these problems and efficiently analyzes Microsoft Windows logs. The proposed model extracts lists of both common and key events from the Microsoft Windows logs to determine detailed actions. In addition, we show an approach based on the proposed model applied to track illegal file access. The proposed approach employs three-step tracking templates using Elastic Stack as well as key-event, common-event lists and identify event lists, which enables visualization of the data for analysis. Using the three-step model, analysts can adjust the depth of their analysis.