• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1231-1234
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• 1992

In this paper a self-tuning control algorithm has been utilized to control speed of a rolling mill DC drive system. Inner current control loop is composed of predictive current controller and the outer speed control loop is composed of the self-tuning PI or IP controller. Computer simulation results reveal that the adaptive control algorithm using self-tuning control is capable of following the typical set point variations required for a rolling mill in conjunction with load torque variations on the shaft of the drive.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.464-467
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• 2002

This paper presents investigation of damping characteristics of squeeze mode type MR (magneto-Rheological) mount experimentally. Since damping property of the MR fluid is changed by variation of the applied magnetic field strength, squeeze mode type MR mount proposed in the study has variable damping characteristics according to the applied magnetic field strength. Impact and excitation tests were performed to investigate the dynamic properties of squeeze mode type MR mount. Responses of the mount were compared in proportion to the applied magnetic field strength. The experimental results show that the mount can effectively reduce vibration amplitude in a wide frequency range by changing the applied magnetic field strength.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.6
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• pp.71-77
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• 1995

This paper deals with design method of learning fuzzy controller for control of an unknown nonlinear plant using the self-tuning algorithm of fuzzy inference rules. In this method the fuzzy identification model obtained that the joined identification model of nonlinear part and linear identification model of linear part by fuzzy inference systems. This fuzzy identification model ordered self-tuning by Decent method so as to be servile to nonlinear plant. A the end, designed learning fuzzy controller of fuzzy identification model have learning structure to model reference adaptive system. The simulation results show that th suggested identification and learning control schemes are practically feasible and effective.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.426-429
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• 1989

The robust self-tuning controller is designed which is guaranteed the asymptotic regulation and tracking in the presence of a bounded parameter perturbation. The global stability in the presence of a finite noise and disturbance is ensured. The controller has a error driven structure, and involves the common model of a disturbance and reference input in the internal model. The adaptive system tunes the controller parameters such that the quadratic performance index which involves a weighting factor is optimized.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.346-350
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• 1989

This paper concerned about a study on the position control of KED-1 robot manipulator using PID self-tuning controller. For two joint manipulator KED-1, KED-1 manipulator is translated into kinematics to control each joints in joint space seheme. Angle displacements of joint coordinate are transformed into reference angle velocity of each subsystem through trajectory planning. Also, time sharing technique is used to control KED-1 manipulator. A series of simulation and experiment are performed for each joint in show the valid of proposed algorithm.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.234-236
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• 2009

종래의 음향기기에서 소리 크기는 각 주파수별로 다른 감도를 갖는 개인의 주파수 청력 특성을 고려하지 않고 모든 주파수에 대하여 동일하게 선형으로 소리 크기를 조절한다. 따라서 감도가 높은 주파수대에서 청력 손상을 일으킨다. 이를 개선하기 위한 표준 청력특성, ISO266:2003 표준을 이용한 평활화 방법이 있지만, 이 표준에 따른 등청감곡선은 여러 사람에 대해 평균한 청력특성이기 때문에 다양한 환경에 의해 변형된 개인별 청력특성에 맞지 않아 청력 손상을 감소시키는 실질적인 효과가 저하되는 문제점이 있다. 본 연구는 사람마다 다른 최소가청한계 특성을 갖는 청각특성과 최대가청한계를 고려하여 소리 크기를 조절함으로써 음향기기에 의한 청각 손상을 감소시키는 방법에 관한 것이다. 컴퓨터 시뮬레이션을 통해 청력 특성이 좋은 대역에서 기존 방법에 비해 보다 낮은 소리 크기에서 불편없이 인지 가능하다는 것을 확인할 수 있었으며, 동시에 과도한 대역별 소리 에너지를 줄여 청각 손상도 방지할 수 있다는 것을 확인할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.376-381
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• 1992

In this thesis, a self-tuning control method based on Variable Structure System technique for tracking control of Direct-Drive motor is presented. The self-tuning control could not make the tracking error zero in the transient period. This tracking error may be due to disturbances or the error in parameter identification. To overcome this problem, a self-tuning control method based on discrete time VSS technique is presented. The STC based on VSS technique gives good tracking performance of the reference signal in the transient period. The proposed controller is robust to parameter errors and disturbances. The performance of the proposed controller is compared with that of simple STC through digital computer simulation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.11
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• pp.1103-1109
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• 2009

In this paper, the control of a membrane used in reverse osmosis desalination plant by using immune algorithm(IA) is addressed. The proposed algorithm IA of auto tuning method can find optimal gains and compared with conventional Ziegler-Nichols tuning method. The results of computer simulation represent that the proposed IA shows a good control performances better than Ziegler-Nichols tuning method.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.279-281
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• 2006

In this paper, we study an approach to design a self-tuning Fuzzy-PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-PI controller for the fire angle control of rectifier.[7] The performance of the Fuzzy-PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain the optimal scaling factors of the Fuzzy-PI controller by Genetic Algorithms. In order to improve Fuzzy-PI controller, we adopt FIS to tune the scaling factors of the Fuzzy-PI controller on line. A comparative study has been performed between Fuzzy-PI and self-tuning Fuzzy-PI controller, to prove the superiority of the proposed scheme.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.325-329
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• 2003

This paper discuss the method of the system's efficient control using a Intelligent hybrid algorithm in nonlinear dynamics systems. Existing neural network and genetic algorithm for the control of non-linear systems work well in static states. but it be not particularly good in changeable states and must re-learn for the control of the system in the changed state. This time spend a lot of time. For the solution of this problem we suggest the intelligent hybrid self-tuning controller. it includes neural network, genetic algorithm and immune system. it is based on neural network, and immune system and genetic algorithm are added against a changed factor. We will call a change factor an antigen. When an antigen broke out, immune system come into action and genetic algorithm search an antibody. So the system is controled more stably and rapidly. Moreover, The Genetic algorithm use the memory address of the immune bank as a genetic factor. So it brings an advantage which the realization of a hardware easy.