• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.6
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• pp.82-86
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• 2005

PID controller is widely used as automatic equipment for industry. However when a system has various characters of intermittence or continuance, a new parameter decision for accurate control is a bud task. As a method of solving this problem, in this paper, a teaming gain regulator as PID controller functions is presented. A propriety teaming gain of system is decided by a rule of Delta learning. The function of proposed loaming gain regulator is verified by simulation results of DC motor.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2839-2842
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• 1999

This paper describes the design of fuzzy PID controller using simplified indirect inference method. First, the fuzzy PID controller is derived from the conventional continuous time linear PID controller. Then the fuzzification, control-rule base, and defuzzification using SIIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional PID controller, which has the same linear structure. but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIIM is applied, the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control performance of the one proposed by D. Misir et al.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2658-2660
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• 2000

본 논문은 주파수역에서의 모델매칭을 이용하여 강인한 성능의 PID 제어기 튜닝법을 제안하였다. 이를 이용하여 부하토크 외란에도 강인한 성능의 BLDC 모터의 속도제어기를 설계하였다. 부하토크 외란이 존재하여도 주어진 기준명령을 강인하게 추종하도록 $H_{\infty}$ 제어를 이용하여 속도제어기를 설계한 후, 설계할 PID 제어계의 루프 전달함수와 설계된 $H_{\infty}$ 제어계의 루프 전달함수간의 오차가 주파수역에서 최소가 되도록 PID 제어기 파라미터를 튜닝하였다. BLDC 모터의 속도제어 시뮬레이션을 통하여 설계된 강인 PID 제어기의 성능을 평가하였다.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1907-1908
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• 2006

Recently, an automatic crane control system is required with high speed and rapid transportation. Therefore, when container is transferred from the initial coordinate to the finial coordinate, the container paths should be built in terms of the least time and without sway. Therefore, we calculated the anti-collision path for avoiding collision in its movement to the finial coordinate in this paper. And we constructed the neural network predictive two degree of freedom PID controller to control the precise navigation. The proposed predictive control system is composed of the neural network predictor, two degree of freedom PID controller, neural network self-tuner which yields parameters of two degree of freedom PID. We analyzed crane system through simulation, and proved excellency of control performance over the conventional controllers.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.194-201
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• 2005

In this paper, we propose an adaptive mechanism based on humoral immune algorithm and neural network identifier technique. It is also applied for an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To slove this problem, we use the neural network identifier technique for modeling the plant humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. Finally, the experimental results for control of steering and speed of AGV system illustrate the validity of the proposed control scheme. Also, these results for the proposed method show that it has better performance than other conventional controller design method such as PID controller.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.769-770
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• 2012

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2501-2504
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• 2003

This paper presents LQ-PID controller to reduce the gap between the input speed and the out speed at the induction motor.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.118-122
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• 2000

Recently, High accuracy and precision are required in various industrial field especially, semiconductor manufacturing apparatus, Ultra precision positioning apparatus, Information field and so on. Positioning technology is a very important one among them. For composition of this technology, the development of system with high speed and high resolution is needed. At start point and end position vibration must be repressed on this system for composition of position control. This vibration is arisen nose, is increased setting time, is reduced accuracy. Especially, repressed for the lead with high speed. The small actuator with high speed and high resolution is need to repression against this residual vibration. This actuator is, for example, piezo actuator, piezoelectric material that converting from electronic signal to mechanical force is adequate material, beacause of control of control to position and force. In this study, piezo electric material is used to actuator, ultra precision positioning apparatus with stage of hinge structure is designed, simulation is performed, control performance is tested by producing apparatus. For easy usage and stability in industrial field, we perform to simulation and to position control test by digital PID controller.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.4
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• pp.414-420
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• 1997

An intelligent speed control system for marine diesel engines is presented. The approach adopt¬ed is to use a conventional PID controller for normal operation and a feedforward controller for adaptive control. The feedforward controller is a neural network. The neural network is the inverse dynamics model of the plant, which is being trained on line. The parametric model of the diesel engine is represented in a linear second-order system, with a first-order combustion part and a revolution part each at a normal operating point. The time delay in the control of the com¬bustion part is approximated to the first-order system. The tuned PID parameters are set based on the model for normal operating point. To obtain the inverse dynamics of the diesel engine system, two neural networks are used, one for inverse, the other for forward dynamics. The former is posi¬tioned across the plant to learn its inverse dynamics during operation, and the latter is placed in series with the controlled plant. Simulation results are presented to illustrate the applicability of the proposed scheme to intelligent adaptive control of diesel engines.

• Proceedings of the KIPE Conference
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• 2011.11a
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• pp.315-316
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• 2011

This paper presents speed control scheme of the PMSM which has torque compensator to reduce the speed error and ripple. The proposed speed controller is based on the conventional PI control scheme. But the additional torque compensator which is different to the conventional differential controller produces a compensation torque to suppress speed ripple. In order to determine the proper compensation, the activation function which has discrete value is used in the proposed control scheme. With the proposed activation function, the compensation torque acts to suppress the speed error increasing. The proposed speed control scheme is verified by the computer simulation and experiments of 400[W] PMSM. In the simulation and experiments, the proposed control scheme has better control performance compare than the conventional PI and PID control schemes.