• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.527-530
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• 1995

In this paper, traffic modeling and control design was considered to analyze and improve the stability of train diagram in the open-loop Metro line. A complete discrete-event traffic model describing the natural instability of open-loop metro line is analyzed. The traffic stability properties are introduced and easy-to-implement state feed back traffic control algorithms are designed, which satisfied with system stability.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1287-1296
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• 2014

This paper is about control of Automated Guided Vehicle for path following using fuzzy logic controller. The Automated Guided Vehicle is a tricycle wheeled mobile robot with three wheels, two fixed passive wheels and one steering driving wheel. First, kinematic and dynamic modeling for Automated Guided Vehicle is presented. Second, a controller that integrates two control loops, kinematic control loop and dynamic control loop, is designed for Automated Guided Vehicle to follow an unknown path. The kinematic control loop based on Fuzzy logic framework and the dynamic control loop based on two PID controllers are proposed. Simulation and experimental results are presented to show the effectiveness of the proposed controllers.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.609-614
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• 1998

A new small signal modeling of an average current mode control is proposed. In order to analyze the characteristics of the control scheme, the discrete and continuous time small signal models are derived. The derivation are mainly come from the analysis of the sampling effect presented in the current control loop. By the mathematical interpretation of practical sampler representing the sampling effect of a current control loop, the small signal models of an average current mode control can be easily derived. The instability of the current control loop, which gives rise to the subharmonic oscillation, can be identified by the proposed models. To show the usefulness of the proposed models, the simulation and experiment are carried out. The results show that the predicted results by the proposed model are much better agreed with the measured ones than that of the conventional model, even though the high gain of the compensation network of a current control loop is employed.

• Journal of Advanced Marine Engineering and Technology
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• v.19 no.2
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• pp.67-80
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• 1995

In order to control systems which are dominantly subjected to modeling errors and uncertainties, control strategies must deal with the effect of modeling errors and uncertainties. Since most of control methods based on system mathematical model, such as LQG/LTR method, have been developed mainly focused on stability robustness, they can not smartly improve the transient response disturbed by modeling errors and/or uncertainties. In this research, a fuzzy PID control method is suggested, which can stably improve the transient responses of systems disturbed by modeling errors as well as systems not entirely using mathematical models. So as to assure the effectiveness of suggested control method, computer simulations are accomplished for some example systems, through the comparison of transient responses.

• Journal of IKEEE
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• v.26 no.4
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• pp.577-583
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• 2022

Verilog-HDL-based modeling can be performed to confirm the fast operation characteristics after setting the design parameters of each block considering the stability of the system by performing linear phase-domain modeling on the phase-locked loop. This paper proposed Verilog-HDL modeling including DCO noise and DTC nonlinear characteristic. After completing the modeling, the time-domain transient simulation can be performed to check the feasibility and the functionality of the proposed PLL system, then the phase noise result from the system design based on the functional model can be verified comparing with the ideal phase noise graph. As a result of the comparison of simulation time (6 us), the Verilog-HDL-based modeling method (1.43 second) showed 484 times faster than the analog transistor level design (692 second) implemented by TSMC 0.18-㎛.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.636-643
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• 1998

This paper is presents multivariable control scheme for industrial robot manipulators. The control scheme consists of two loops. The modeling error between linearized robot model and actual robot model is compensated in error compensation loop. The PID control loop is designed for pole assignment to stability of robot system and utilized for trajectory tracking. Alternatively computer simulation results are given for illustration purpose of suggested controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.142-147
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• 2003

We consider a single-input-single-output nonlinear system which can be represented in a normal form. The nonlinear system has a modeling uncertainties including the input coefficient uncertainty. A high-gain observer is used to estimate the states variables to reject a modeling uncertainty. A globally bounded output feedback integral sliding mode control is proposed to stabilize the closed loop system. The proposed integral sliding mode control can asymptotically stabilize the closed loop system in the presence of input coefficient uncertainty.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.191-196
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• 2010

In this paper, modeling of the non-ideal frequency response, especially "notch-and-spike" magnitude phenomenon and phase lag distortion, are discussed. To characterize the non-ideal frequency response, a new electro-mechanical simulation model based on SPICE is proposed using the driving loop of the capacitive vibratory gyroscope. The parasitic components of the driving loop are found to be the major factors of non-ideal frequency response, and it is verified with the measurement results.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.29-38
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• 1997

A closed-loop system modeling of an active/semiactive suspension system has been accomplished through an artificial neural network. A 7DOF full model as a system's equation of motion has been derived and an output feedback linear quadratic regulator has been designed for control purpose. A training set of a sample data has been obtained through a computer simulation. A 7DOF full model with LQR controller simulated under several road conditions such as sinusoidal bumps and rectangular bumps. A general multilayer perceptron neural network is used for dynamic modeling and target outputs are fedback to the a layer. A backpropagation method is used as a training algorithm. Model validation of new dataset have been shown through computer simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.384-388
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• 1996

The closed-loop system modeling of an Active/semiactive suspension system has been accomplished through an artificial neural Networks. The 7DOF full model as the system equation of motion has been derived and the output feedback linear quadratic regulator has been designed for the control purpose. For the neural networks training set of a sample data has been obtained through the computer simulation. A 7DOF full model with LQR controller simulated under the several road conditions such as sinusoidal bumps and the rectangular bumps. A general multilayer perceptron neural network is used for the dynamic modeling and the target outputs are feedback to the input layer. The Backpropagation method is used as the training algorithm. The modeling of system and the model validation have been shown through computer simulations.