• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1062-1073
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• 2004

We describe a looper controller design for a hot strip finishing mill in steel plants. The main function of the looper system is to balance the mass flow of the strip by accumulating material in the middle of the stands. Another function is to control the strip tension which influences the width of the strip. To ensure strip quality, it is very important to control the tension of the hot strip finishing mill. However, because there is a mutual interaction between the looper angle and the strip tension, it is difficult to control the looper system. Previous researches examined only the operation of a single stand. But it is not sufficient to examine the operation and effect of whole stands because the operation is wholly interdependent. In this paper, we present a full model of the hot strip finishing mill in order to more effectively control strip tension. We propose several control methods for the full-stand hot strip finishing mill, denoted as conventional PI, PI with cross gain, and coefficient diagram method (CDM) PID control. In the real plants, there are some problems by using higher order controllers such as LQ, LQG and H$\_$$\infty$/. By comparison, the PID controller is very simple and easy to apply to all real plants. To that end, we present our findings on PID controls and their potential use in the hot strip finishing mill.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.587-590
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• 2003

In this paper, the control of the differential drive wheeled mobile robot (DDWMR) is studied. Because the DDWMR have non-holonomic constraints, it cannot be stabilized by smooth feedback. The T-S fuzzy model for the DDWMR is presented and a control algorithm Is developed by well known PID control and LMI based regional pole-placement.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.135-138
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• 2002

본 논문에서는 비최소위상 시스템으로 표현되는 화력발전소 드럼의 수위제어를 위한 퍼지 제어기를 제안한다. 제안된 방법은 T. Takagi와 M. Sugeno의 퍼지모델을 기반으로 수행된다. 그리고 기존의 PID 및 LQ 제어기법을 적용한 방식과 비교하여 제안된 방법의 개선된 특성을 시뮬레이션 결과로부터 검증하였다.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.3
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• pp.320-327
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• 1998

The purpose of this study is to design the intelligent speed control system for marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. Recently for the speed control of a diesel engine some methods using the advanced control techniques such as LQ control Fuzzy control or H$\infty$ control etc. have been reported. However most of speed controllers of a marine diesel engine developed are still using the PID control algorithm But the performance of a marine diesel engine depends highly on the parameter setting of the PID controllers. The authors proposed already a new method to tune efficiently the PID parameters by the Model Mathcing Method typically taking a marine diesel engine as a non-oscillatory second-order system. It was confirmed that the previously proposed method is superior to Ziegler & Nichols's method through simulations under the assumption that the parameters of a diesel engine are exactly known. But actually it is very difficult to find out the exact model of the diesel engine. Therefore when the model and the actual diesel engine are unmatched as an alternative to enhance the speed control characteristics this paper proposes a Model Refernce Adaptive Speed Control system of a diesel engine in which PID control system for the model of a diesel engine is adopted as the nominal model and a Fuzzy controller is adopted as the adaptive controller, And in the nominal model parameters of a diesel engine are adjusted using the Model Matching Method. it is confirmed that the proposed method gives better performance than the case of using only Model Matching Method through the analysis of the characteristics of indicial responses.

• 연구논문집
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• s.23
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• pp.73-80
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• 1993

This study presents an intelligent PID control method based on the fuzzy logic and this method is applied to the active magnetic bearing system. By using an appropriate fuzzy matrix, some changes of values of the three coefficients of the controller are determined during system operation and these lead to the improvement of the transient and steady state behavior of the closed loop system. The presented method is actually a combination of the principles of PID control and fuzzy logic. Since the fuzzy logic using linguistic variables in place of numeric variables has many points of likeness to the human logic, the improvement in performance is notable especially in case of large nonlinearity and uncertainty such as the controller start and the excessive mass unbalance. A set of simulation and experimental results illustrate and considerable improvement in the control performance including small overshoot and small transient currents in magnet coils, while maintaining the overal static and dynamic characteristics near the equilibrium position.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.101.3-101
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• 2002

Contents 1 Abstract- In the thermal power plant, there are six manipulated variables; main steam flow, feedwater flow, air flow, spray flow, fuel flow, and gas recirculation flow. Therefore, the thermal power plant control system is a multi-input and output system. In the control system, the main steam temperature typically is regulated by the fuel flow rate and the spray flow rate, and the reheater steam temperature is regulated by the gas recirculation flow rate. Up to the present time, the PID controller has been used to operate this system. This paper focuses on the characteristic comparison of the PID controller, the modified 2-DOF PID Controller on the DCS, in order to design an optimal...

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.798-800
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• 1998

In recent years, advances in construction techniques and materials have given rise to flexible light-weight structures. Because these structures extremely susceptib environmental loads, these random loadings u produce large deflection and acceleration on structures. Vibration control system of structur becoming an integral part of the structural syst the next generation of tall building. The proposed control system is applied to s degree of structure with mass damping and com with conventional PID and neural network PID system.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2129-2131
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• 2001

Induction motor has been using for industrial field. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the fuzzy control for optimal control of the induction motor in plant. In order to attain optimal control, flux, torque and speed controller has been used and an fuzzy logic based controller has been applied to this system. The results of the fuzzy are compared with the PID controller tuned by the Ziegler-Nickels method, through various simulation based on the various disturbance and step response. The simulation results of the fuzzy control represent a more satisfactory response than those of the conventional controllers.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.321-328
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• 1998

When we control the level of the steam generator in the nuclear power plants, a swell and shrink arises from many disturbances such as feed water rate, feed water temperature, main steam flow rate, and coolant temperature. If we use the conventional type of PI controller in this system, we will not have stability during controlling at lower power, the removal function of disturbances, and a load follow-up control effectively. In this paper, we study the application of a 2-Degree of Freedom(2-DOF) PID controller to the level control of the steam. generator of nuclear power plants through the simulation and the experimental steam generator. We use the parameters $\alpha$, $\beta$, $\gamma$ of the 2-DOF PID controller for the removal of disturbances and the parameters Kp,Ti,Td of the conventional type of PID controller for controlling setpoint. The back-propagation learning algorithm of neural network is used for tuning the 2-DOF PID controller. We can find satisfactory results of the removal of the disturbances and the tracking function in the change of setpoint through the simulation and experimental steam generator.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.139-148
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• 2024

In this paper, we propose a two-degree-of-freedom snake robot head system and an I-PID (Intelligent Proportional-Integral-Derivative)-based controller utilizing RBF (Radial Basis Function) neural network and adaptive robust terms as a control strategy to reduce rotation occurring in the snake robot head. This study proposes a two-degree-of-freedom snake robot head system to avoid complex snake robot dynamics. This system has a control system independent of the snake robot. Subsequently, it utilizes an I-PID controller to implement a control system that can effectively manage rotation at the snake robot head, the robot's nonlinearity, and disturbances. To compensate for the time delay estimation errors occurring in the I-PID control system, an RBF neural network is integrated. Additionally, an adaptive robust term is designed and integrated into the control system to enhance robustness and generate control inputs responsive to signal changes. The proposed controller satisfies stability according to Lyapunov's theory. The proposed control strategy was tested using a 9-degreeof-freedom snake robot. It demonstrates the capability to reduce rotation in Lateral undulation, Rectilinear, and Sidewinding locomotion.