• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.1
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• pp.8-16
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• 1986

For digital process control, a low order discrete time modeling method is suggested and a direct digital control algorithm has been developed. The modeling method maintains process order of 3, while the sampling rate is doubled for fast response. With easy calculation it is possible to compute the model parameters and the controller gains. Controller tuning is possible on the spot. Simulation results show that this method has better performance than the deadbeat control agorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.1069-1076
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• 2012

We use largely two methods, how to control the noise of the KTX, they are the passive noise control method and the active noise control method. The passive noise control has been used in a variety of ways since the KTX opening day, but lately it has shown the technical limitations by being dropped sharply. So, it is getting important to conduct the research about ANC that is able to reduce the ambient noise when the environmental-factor changes and be installed easily. To reduce a three-dimensional closed-space sound field like a car of a high-speed rail is hard to do using single channel ANC control system. Therefore we have to model the paths of the noise exactly for reducing the noise. And the control speakers and the error mics should be designed for optimal position. In this paper, we designed the transfer functions for modeling the noise paths under the influence of the distance between control speakers & error mics and primary noise speaker in TEST-BED where there is modeled as actual interior of KTX. We have made the modeling and the simulations of interior environment of KTX car by using three frequency bands of 120Hz, 280Hz, 360Hz. After the modeling, we compared the performance of active noise control and also we analyzed what to affect with difference in distance. After comparing of the performance using Pure Tone 120Hz, 280Hz, 360Hz at each modeling and then we simulated ANC for KTX's interior noise which we measured really and analyzed.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.183-192
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• 2003

Obstacle detection and avoidance are considered as one of the key technologies on an unmanned vehicle system. In this paper, we propose a method of obstacle detection and avoidance and it is composed of vehicle control, modeling, and sensor experiments. Obstacle detection and avoidance consist of two parts: one is longitudinal control system for acceleration and deceleration and the other is lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control system of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are evaluated through road tests.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.239-244
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• 2009

This paper suggests a precision positioning control technique of a precision positioning stage with coupling effects. The precision positioning stage is supported by four flexible spring hinges and driven by two piezoelectric actuators. The dynamic characteristics of the precision positioning stage is modeled and identified by the FEM analysis. The dynamic characteristics of the stage are also identified by the frequency domain modeling technique based on the experimental data. Reliability of two modeling methods is examined by comparing the numerically and experimentally produced responses of the stage. This paper proposes a sliding mode control technique with integrator to improve the tracking ability of the precision positioning stage to the complex input signal using. To demonstrate the effectiveness of the proposed modeling schemes and control algorithm, experiment validations are performed.

• International Journal of Automotive Technology
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• v.4 no.4
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• pp.173-180
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• 2003

Obstacle avoidance is considered as one of the key technologies in an unmanned vehicle system. In this paper, we propose a method of obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. Obstacle avoidance consists of two parts: one longitudinal control system for acceleration; and deceleration and a lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. The method proposed for vehicle control, modeling, and obstacle avoidance has been confirmed through vehicle tests.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.22-29
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• 2003

A piezoelectric actuator yields hysteresis effect due to its composed ferroelectric. Hysteresis nonlinearty is neglected when a piezoelectric actuator moves with short stroke. However when it moves with long stroke and high frequency, the hysteresis nonlinearty can not be neglected. The hysteresis nonlinearty of piezoelectric actuator degrades the control performance in precision position control. In this paper, in order to improve the control performance of piezoelectric actuator, an inverse modeling scheme is proposed to compensate the hysteresis nonlinearty. And feedforward - feedback controller is proposed to give a good tracking performance. The Feedforward controller is an inverse hysteresis model, base on neural network and the feedback control is implemented with PID control. To show the feasibility of the proposed controller and hysteresis modeling, some experiments have been carried out. It is concluded that the proposed control scheme gives good tracking performance.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.6
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• pp.51-58
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• 2010

This paper suggests a control technique of the two axes precision stage. The stage is supported by four flexible spring hinges and driven by two piezoelectric actuators. The dynamic motion of the stage is analysed by the finite element method and identified by the frequency domain modeling technique based on the experimental data. The sliding mode control with integrator is applied to improve the tracking ability of the stage to the complex reference input signal. Experimental results demonstrate that the proposed modeling schemes and control algorithm can be used effectively for the two axes stage.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.325-328
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• 1997

In this paper the modeling and control of a twin roll strip caster is investigated. Mathematical models for the strip casting process are obtained by analyzing five critical areas such that the molten steel level in the pool, solidification process, roll separating force and torque, roll dynamics including hydraulic actuators, and roll drive system. A two-level control strategy is proposed. At lower level, three local subsystems are independently feedback-controlled by suitable local controllers which perform well to the behaviors of each subsystem. They are a variable structure control of the molten steel level in the pool, an adaptive predictive control of the roll gap which is directly related to the strip thickness, and an $H^{\infty}$ control of the roll drive system. At higher level, all reference signals to the lower level subsystems are generated by an optimal controller in the perspective of regulating the strip thickness and roll separating force. Simulations are provided..

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1012-1015
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• 1996

This study focuses on the optimal operation and control strategy of the fuel cell process. The control objective of the Phosphoric Acid Fuel Cell (PAFC) is established and dynamic modeling equations of the entire fuel cell process are formulated as discrete-time type. On-line optimal control of the MIMO system employs the direct decomposition-coordination method. The objective function is modified as the tracking form to enhance the response capability to the load change. The weight factor matrices Q,R, which are design parameters, are readjusted. This control system is compared with LQI method and the results show that the suggested method is better than the traditional method in pressure difference control.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.1
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• pp.67-76
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• 2012

This paper proposes the aggregated modeling and control of integated boost-flyback converter (IBFC) for understanding of dynamics characteristic and designing of relevant controller. The basic concept of the aggregated modeling is to substitute the boost or the flyback converter with an equivalent current source. Since each converter with equivalent current source corresponds to the basic boost and flyback converters, the overall mathematical process is significantly simplified for the modeling. Afterwards each result is combined to construct the complete model of the IBFC, and the relevant controller is designed through the achieved small-signal model. Simulation and experimental results show excellent agreement with the theoretical expectations.