• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.171-174
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• 2007

A realization for FF-PID(Feed-Forward PID) controlling system with backward propagation algorithm and image pattern recognition is presented in this paper. The pattern recognition used backward propagation of nervous network is teaming. FF-PID is enhanced the response characteristic of moving image by using the controlling value which is output error for the target value of nervous system. In conclusion of experiment, the system is shown that the response is worked as 2.7sec that is enhanced round 15% in comparison with general difference image algorithm. The system is able to control a moving object with effect.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.961-964
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• 2016

This paper describes the implementation of AUSV system for Sonar Image acquisition. The system be controlled by FF-PID algorithm for the thrusters using motion sensor and DGPS. As experimental results, the control performance is that the error distance from the destination positions are under 5m in total survey track of 1km, and the image deviation is under 12 pixel from the manned survey method, which the comparison with the total image quality is almost the same as the manned survey one. Thus the AUSV system is a new method of system can be utilized on the limited survey area as the surveyor should not be able to approach on sea surface.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2089-2092
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• 2002

The PID controller have the simple structure and show the comparatively good control performance. Crystal Grower(FF-CZ150) melt polycrystalline silicon at the temperature of about 1450$^{\circ}C$, then grow it into a single crystalline ingot. The automatic diameter control system of the Crystal Grower has a good performance with only PD control. But it contain the integrator in the plant which has a long time delay. In this paper, we show the secondary approximate model and applies time delay controller which has good performance for the plant with long time delay. It will be able to improve the response characteristic against a standard input and a load disturbance.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.25-34
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• 2000

In this paper, we design a H^\infty servo controller for gauge control of tandem cold mill. To improve the performance of the AGC(Aotomatic Gauge Control) system based on the Taylor linearized model of tandem cold mill, the H^\infty servo controller is designed to satisfy robust stability, disturbance attenuation and robust tracking properties. The H^\infty servo controller problem is modified as an usual H^\infty control problem, and the solvability condition of the H^\infty servo problem depends on the solvability of the modified H^\infty control problem. Since this modified problem does not satisfied standard assumptions for the H^\infty control problem, it is solved by an LMI(Linear Matrix Inequality) technique. Consequently, the comparison between the H^\infty servo controller and the existing PID/FF(FeedForward) controller shows the usefulness of this study.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.2
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• pp.74-80
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• 2003

In this paper, a robust two-degree-of-freedom(TDF) the speed control system using $H_{\infty}$ optimization method and real genetic algorithm is proposed for the robust stability and the robust performance in dc servo motor system. This control system composed of feedback and feedforward controller. The feedback(FB) controller with $H_{\infty}$ optimization method is designed for real genetic algorithm that is model matching problem using mixed sensitivity function. The feedforward(FF) controller with $H_{\infty}$optimization method is minimized the error between transfer function of the optimal model and the overall transfer function. The proposed robust two-degree-of-freedom speed control system is simulated to the dc servo motor. By the simulation, feedback controller can obtain the robust stability property and feedforward controller can obtain the robust performance property under modelling error. The performance of the dc servo motor is analyzed by the experiment setting. The validity of the proposed method is verified through being compared with pid(proportional integrated differential)control system design method for the dc servo motor.