• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.24-32
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• 2003

The PID controller has been widely used in industrial applications due to its simple structure and robustness. Even if it is initially well tuned, the PID controller must be retuned to maintain acceptable performance when there are system parameter changes due to the change of operation conditions. In this paper, a self-tuning control scheme which comprises a parameter estimator, a NN-based rule emulator and a PID controller is proposed, which can cope with changing environments. This method involves combining neural networks and real-coded genetic algorithms(RCGAs) with conventional approaches to provide a stable and satisfactory response. A RCGA-based parameter estimation method is first described to obtain the first-order with time delay model from over-damped high-order systems. Then, a set of optimum PID parameters are calculated based on the estimated model such that they cover the entire spectrum of system operations and an optimum tuning rule is trained with a BP-based neural network. A set of simulation works on systems with time delay are carried out to demonstrate the effectiveness of the proposed method.

• Nuclear Engineering and Technology
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• v.27 no.6
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• pp.833-844
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• 1995

In self-tuning predictive control algorithm for steam generator is presented. The control algorithm is derived by suitably modifying the generalized predictive control algorithm. The main feature of the unposed method relies on considering the measurable disturbance and a simple adaptive scheme for obtaining the controller gain when the parameters of the plant are unknown. This feature makes the proposed approach particularly appealing for water level control of steam generator when measurable disturbance is used. In order to evaluate the performance of the proposed algorithm, computer simulations are done for an PWR steam generator model. Simulation result show satisfactory performances against load variations and steam flow rate estimation errors. It can be also observed that the proposed algorithm exhibit better responses than a conventional PI controller.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.12
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• pp.1091-1097
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• 2011

In the present study, TMD(tuned mass damper) with eddy current damping is proposed to suppress the vibration of a cantilever beam effectively. The advantages of TMD are that it is simple and its performance are excellent at any particular frequency. However, TMD may have the low performance at other frequency. To solve this problem and improve its performance, this study applies the eddy current damping to TMD. This TMD with ECD is named as MTMD(magnetically tuned mass damper). MTMD is designed for the vibration suppression of a cantilever beam. The mathematical modeling, simulation, and experiments of the cantilever beam with MTMD are performed. From analytic and experimental results, it can be concluded that the vibration suppression performance of MTMD are excellent.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.2
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• pp.209-214
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• 1999

New estimation and tuning schemes of inductance variations for rotor flux oriented (RFO) control of induction motor in field weakening region are presented. Stator transient inductance and stator self inductance are estimated. From estimated stator self inductance. magnetizing inductance is estimated and from estimated stator transient inductance, rotor leakage inductance is estimated. Simulation and experimental results prove the effectiveness of the proposed s scheme in constant torque and field weakening region.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.150-155
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using digital signal processors for robot manipulators. TMS3200C50 is used in implementing real-time adaptive control algorithms provide advanced performance for robot manipulator. In this paper an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm and controller parameters are detemined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.8
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• pp.708-714
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• 1990

This paper has proposed a self-tuning controller for tracking reference trajectory by measuring End-point of arm on robot manipulator whose link is light and flexibls, and proved the perforformance of the algorithm proposed through the computer simulation. As an object of control, a flexible robot manipulator with two-links was selected. As for structure of model, it utilized an assume mode shape method with include travity force and derived a dynaics equation by adapting two kinds of vibration mode of each.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.168-175
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• 1995

A robust speed control algorithm under disturbances and reference change is developed using the self tuning control method in order to control induction motors. The method incorporates the concepts of the well known internal model principle and the annihilator polynomial. The effectiveness of the method is evaluated through the speed control experimental results of an induction motor for refernce change and arbitrary distrbance.

• Proceedings of the KIEE Conference
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• 1984.07a
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• pp.33-35
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• 1984

• Review of KIISC
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• v.1 no.2
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• pp.9-28
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• 1991

창간호에 이어 본고에서는 동기축자암호시스템(synchronous stream ciphers)의 암호 화 및 복호, 키 자동키 암호시스템, 그리고 자기동조축자암호시스템의 암호문귀환암호시스 템과 평문귀환암호시스템에 관하여 분석하고자 한다.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.629-632
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• 1997

This paper presents the design method of controller which is combined Genetic Algorithms with the Generalized minimum variance self tuning controller. It is shown that the controllers adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a polynomial parameters. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.