• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1014-1019
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• 2005

In this paper, a neural network technique for automatic steering control of a four wheel drive autonomous highway snowplow vehicle is presented. Controllers are designed by the LQR method based on the vehicle model. Then, neural network is used as an auxiliary controller to minimize lateral tracking error under the presence of load. Simulation studies of LQR control and neural network control are conducted for the vehicle model under a virtual snowplowing situation. Tracking performances are also compared for two and four wheeled steering vehicles.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1171-1172
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• 2008

In this paper, we investigate the issues on the design and implementation of tele-operation system based on the haptic interface. Here, the 3-DOF haptic device and the X-Y-Z stage are employed as master controller and slave system respectively. For this master-slave system, the force feedback algorithm, the modeling of virtual environments and the control method of X-Y-Z stage are presented. In this paper, internet network is used for data communication between master and slave.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.871-878
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• 2003

With the development of micro -technology, the demand for micro actual ing device is increasing. But, it is difficult to achieve high resolution and wide bandwidth with the conventional contact systems. So, the contact-free systems which are suspended or levitated by magnetic force or air bearing were proposed. These systems can be applied to high precision stages and alignment apparatuses. This paper describes a magnetically suspended system with four degrees of freedom which are composed of three rotations (roll, pitch, yaw), and one translation ( z). The operating principle and the structure of the system are similar to variable reluctance type electric machines. In this study, the force analysis is executed using magnetic circuit and virtual work principle, and the equations that describe the dynamics of the system are presented. The multivariable PID controller is adapted to the system and the experiment is executed.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.6
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• pp.553-562
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• 2015

This paper presents a strategy and an algorithm for levitation control of an over-actuated passive maglev tray system. The passive maglev tray system has more actuators than its degrees of freedom. The actuators of the system are switching when the tray travels longitudinally. Furthermore, the levitation forces of the actuators are non-homogeneous because the actuation devices are not in the moving platform. These characteristics make a limit in using conventional control approaches for levitation. For smooth actuator switching, the actuator force generation should be dependent on longitudinal positions of the tray. To enable constant pose tracking, this research introduces a control strategy and a control algorithm based on integral controllers on virtual variables. The states of the tray are estimated using a Kalman filter and fed to the proposed controller. The performances of the proposed control strategy and the algorithm are validated through tests.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.11a
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• pp.228-230
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• 2000

본 연구에서는 시청각 위주의 VR 멀티미디어 환경에 후각자극을 제시함으로써 더욱 현장감 있는 상황을 느낄 수 있는 칩타입 향 발생장치를 개발하였다. 셀마다 향과 Heating Coil을 함유하고 있는 IC 타입의 향 Container, DC Motor와 IC Holder를 포함하는 향 Housing, 전체적인 제어를 담당하는 Hardware Controller와 후각정보가 Encoding된 멀티미디어로 구성된다. 멀티미디어 매체 제작시 각 Object에 대한 Bounding Box를 설정하여 해당 영역에서만 향이 발산되도록 하였고 향발생장치를 Virtual Driving Simulator에 적용하여 화면의 영상과 함께 해당 향이 잘 발산되어 더욱 현실감 있는 VR 멀티미디어를 구현하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.842-847
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• 2002

One of the challenging problems with bicycle simulators is to deal with the inherent unstable bicycle dynamics that is coupled with rider's motion. For the bicycle dynamics calculation and the real time simulation, it is necessary to identify the control inputs from the rider as well as the virtual environments. The six control forces of the Stewart platform-based motion system are used for estimation of the rider's action force, which is one of the important control inputs, but of which the direct measurement is impractical. For the effective estimation of the rider's action force, the dynamics model of the motion system is derived incorporated with both analytical and experimental methods and the sliding mode controller with perturbation estimation is developed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.69-75
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• 2005

In this paper, the feedback linearization technique is used with the sliding mode control for nonlinear systems. This combination of the two control techniques is achieved by introducing a novel sliding surface which has the nominal dynamics of the original system controlled by feedback linearization technique. Its design is based on the augmented system whose dynamics have a higher order than that of the original system. The reaching phase is removed by using an initial virtual state which makes the initial sliding function equal to zero.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.3
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• pp.28-34
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• 2006

An ACC driving simulator is a virtual reality device which designed to test or evaluate vehicle control algorithm. It is designed and built based on the rapid control prototyping(RCP) concept. Therefore this simulator adopt RCP tools to solve the equation of a vehicle dynamics model and control algorithm in real time, rendering engine to provide real-time visual representation of vehicle behavior and CAN communication to reduce networking load. It can provide also many different driving test environment and driving scenarios.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.5-11
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• 2010

An adaptive formation control approach is proposed for nonhonolomic multiple mobile robots considering unknown slipping and skidding. It is assumed that unknown slipping and skidding effects are bounded by unknown constants. Under this assumption, the adaptive technique is employed to estimate the bounds of unknown slipping and skidding effects of each mobile robot. To deal with the skidding effect included in kinematics, the dynamic surface design approach is applied to design a local controller for each mobile robot. Using Lyapunov stability theorem, the adaptation laws for tuning bounds of slipping and skidding are induced and it is proved that all signals of the closed-loop system are bounded and the tracking errors and the synchronization errors of the path parameters converge to an adjustable neighborhood of the origin. Finally, simulation results are provided to verify the effectiveness of the proposed approach.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.