• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.131-134
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• 1997

This paper presents a new approach to the design of intelligent control system for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.70-75
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• 1997

This paper proposes a new approach to the design of fuzzy-neuro control for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• International Journal of High-Rise Buildings
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• v.11 no.3
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• pp.207-219
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• 2022

During the structural design of urban over-track high-rise buildings, two problems are most likely encountered: the abrupt change of story stiffness between the podium and the upper towers, as well as the demand for train-induced vibration control. Traditional earthquake-resistant structures have to be particularly designed with transfer stories to meet the requirement of seismic control under earthquakes, and thus horizontal seismic isolation techniques are recommended to solve the transfer problem. The function of mitigating the vertical subway-induced vibration can be integrated into the isolation system including thick rubber bearings and 3D composite vibration control devices. Engineering project cases are presented in this paper for a more comprehensive understanding of the engineering practice and research frontiers of urban over-track high-rise buildings in China.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.68-75
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• 1997

This paper presents a new approach to the design of neural-fuzzy controller for the speed and azimuth control of a track vehicle. The proposed control scheme uses a Gaussian function as a unit function in the frzzy-neural network, and back propagaton algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a track vehicle driven by two independent wheels.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1710-1715
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• 2005

Two fuzzy controllers are coordinated to control a cartpole such that the pole is balanced as well as the cart is brought back to the track origin. The coordination is due to the BOXES scheme that is established through the evaluation of the outcomes of the control action by one of the fuzzy controllers. It is found that the control scheme is good at selecting proper fuzzy controller so that the pole is balanced fast while the cart moves back to the track origin steadily.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.117-123
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• 2003

Rotational machines such as optical disk drives, hard disk drives, and so on are subject to periodic disturbances caused by their mechanical characteristics. In the meanwhile, it is well known that repetitive control rejects periodic disturbance effectively. This paper presents a practical application of repetitive control to the track-following servo of an optical disk drive. The repetitive control system is composed of two repetitive controllers which compensate for periodic disturbances generated by track geometry and eccentric rotation of disk and a feedback controller stabilizing the feedback loop. A robust stability for all plant uncertainties is proved using linear matrix inequalities (LMIs). In the controller design, a weighting function is introduced for the feedback controller to ensure a minimum loop gain and a sufficient phase margin. The repetitive controllers and the feedback controller are designed by solving an optimization problem which can consider the robust stability condition and the system performance. The developed repetitive control system is implemented in the digital control system with a 16-bit fixed-point digital signal processor (DSP). Through simulation and experiment. The feasibility of the proposed repetitive control system is verified.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.162-169
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• 2016

Gyeong-bu railway line in Korea between Seoul and Cheon-an was built as two double tracks. A four-display signaling system, only for the metro line, was installed on the second double track so KTX and conventional trains can only operate on the first double track. This study suggests a method to allow KTX and conventional trains operated on the five-display signaling system to respond to accidents and track defects on the second double-track under the four-display signal system by means of problem analysis, calculation of breaking distances for KTX and conventional trains at each break mode, and improvement of the ATS system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.237-242
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• 2000

The areal recording density of HDD(Hard Disk Drive) has been increasing by about 60% a year. In order to achieve high areal density, less track pitch is expected and more servo bandwidth is required. Dual stage actuator and servo controller for HDD have been suggested for achieving high track density as a possible solution. Dual-loop servo system is generally classified into a two-input-two-output system, but if we use an estimator for a two-input-two-output system, it can be converted into two input one output system. Since we can't control the dual stage servo system by the classical method, it requires a special technique; for example, Parallel Loop System, Master-Slave Loop System, Decoupled Master-Slave Loop System, and Dual Feedback Loop System. In this paper, we performed experimental evaluations of several types of control algorithm. Further experiments will be made in the future.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.107-111
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• 1998

This paper presents a now approach to the design of intelligent contorl system for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. Moreover, We develop a Windows 95 version dynamic simulator which can simulate a track vehicle model in 3D graphics space. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The dynamic simulator for track vehicle is developed by Microsoft Visual C++. Graphic libraries, OpenGL, by Silicon Graphics, Inc. were utilized for 3D Graphics. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.210-215
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• 1999

In this paper, a new approach to the dynamic control technique for track vehicle system using fuzzy-neural network control technique is proposed. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle.