• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.6
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• pp.1-8
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• 2002

This paper presents a generalized minimum-variance self-tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior and time delays. The neural network is used to estimate the controller parameters, and the control output is obtained through estimated controller parameter. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation is done to adapt the nonlinear nonminimum phase system with time delays and changed system parameter after a constant time. The proposed method compared with direct adaptive controller using neural network.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.3
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• pp.143-149
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• 2018

It has become ever harder to design reliable circuits with each nanometer technology node; under normal operation conditions, a transistor device can be affected by various aging effects resulting in performance degradation and eventually design failure. The reliability (aging) effect has traditionally been the area of process engineers. However, in the future, even the smallest of variations can slow down a transistor's switching speed, and an aging device may not perform adequately at a very low voltage. Therefore, circuit designers need to consider these reliability effects in the early stages of design to make sure there are enough margins for circuits to function correctly over their entire lifetime. However, such an approach excessively increases the size and power dissipation of a system. As the impact of reliability, new techniques in designing aging-resilient circuits are necessary to reduce the impact of the aging stresses on performance, power, and yield or to predict the failure of a system. Therefore, in this paper, a novel low power on-chip self-tuning circuit considering the aging effects has been proposed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.175-181
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• 2009

In this paper, it is suggested that the selection method of parameter of Power System Stabilizer(PSS) with robustness in low frequency oscillation for Static VAR Compensator(SVC) using a self tuning fuzzy controller for a synchronous generator excitation and SVC system. The proposed parameter self tuning algorithm of fuzzy controller is based on the steepest decent method using two direction vectors which make error between inference values of fuzzy controller and output values of the specially selected PSS reduce steepestly. Using input-output data pair obtained from PSS, the parameters in antecedent part and in consequent part of fuzzy inference rules are learned and tuned automatically using the proposed steepest decent method.

• Proceedings of the KIEE Conference
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• 2005.10a
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• pp.136-138
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• 2005

The conventional self-tuning methods have the speed control problem of nonlinear BLDC motor which can't adapt against any kinds of noise or operation circumstances. In this paper, supposed to solve these problem to PI parameters controller algorithm using ANN. In the proposed algorithm, the parameters of the controller were adjusted to reduce by on-line system the error of the speed of BLDC motor. In this process, EBPA NN was constituted to an output error value of a BLDC motor and conspired an input and output. The performance of the self-tuning controller is compared with that of the PI controller tuned by conventional method(Z&N). The effectiveness of the proposed control method IS verified thought the Matlab Simulink.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.160-166
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• 2005

In this paper, to overcome drawbacks of FLC a self tuning fuzzy sliding mode controller is proposed, which controls the position of excavator's attachment, which can be regarded as an ill-defined system. It is reported that fuzzy logic theory is especially useful in the control of ill-defined system. It is important in the design of a FLC to derive control rules in which the system's dynamic characteristics are taken into account. Control rules are usually established using trial and error methods. However, in the case where the dynamic characteristics vary with operating conditions, as in the operation of excavator attachment, it is difficult to find out control rules in which all the working condition parameters are considered. Experiments are carried out on a test bed which is built around a commercial Hyundai HX-60W hydraulic excavator. The experimental results show that both alleviation of chattering and performance are achieved. Fuzzy rules are easily obtained by using the proposed method and good performance in the following the desired trajectory is achieved. In summary, the proposed controller is very effective control method for the position control of the excavator's attachment.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.29-38
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• 1998

This paper proposes the neural network self-tuning PID controller for the load frequency control of 2- areas power system, namely, the prompt convergence of frequency and tie-line power flow deviation. The neural network applied to computer simulation consists of neurons of two inputs, ten hiddens and tliree outputs layer. Neurons of two inputs layer receive the error and its change rate of the system and cutputs layer consists of three neurons for the parameters of the PID controller. The simulation results shows that the proposed neural network self-tuning PID controller is superior to conventional control t~:chniques(Optimal, PID) in dynamic response and control performance.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.39-46
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• 2022

In this paper, we propose a multi-task model that can simultaneously predict general-purpose tasks such as part-of-speech tagging, lemmatization, and dependency parsing using the UD Korean Kaist v2.3 corpus. The proposed model thus applies the self-attention technique of the BERT model and the graph-based Biaffine attention technique by fine-tuning the multilingual BERT and the two Korean-specific BERTs such as KR-BERT and KoBERT. The performances of the proposed model are compared and analyzed using the multilingual version of BERT and the two Korean-specific BERT language models.

• Korean Journal of Optics and Photonics
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• v.17 no.6
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• pp.548-555
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• 2006

We investigate the effect of the reflectivity of both facets and the phase of a phase tuning section on the self-pulsation (SP) characteristics of multisection index-coupled (IC) DFB lasers composed of two index-coupled DFB sections and a phase tuning section between them in terms of yield. In the case of weak coupling strength, as the reflectivity of both facets increases, the effect of reflected fields from both facets and the other DFB section on the mode characteristics of one DFB section increases. Thus the number of mode hoping increases and yield decreases for the variation of phases of both facets. In the case of strong coupling strength, as the reflectivity of both facets increases, the spatial hole burning effect increases, so that the yield decreases. The maximum yield and the range of the phase of a phase tuning section with yield more than 40% decrease as the facet reflectivity increases irrespective of coupling strength. As the coupling strength increases, the variation of yield for the variation of the phase of a phase tuning section increases and the variation of the phase of a phase tuning section with the maximum yield for the variation of the reflectivity of both facets decreases. The yield characteristics of the cases with the coupling strengths of 2 and 3 are better than those with the coupling strengths of 1.2 and 4.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.260-262
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• 2006

This paper presents Hybrid-PI controller of induction motor drive using fuzzy control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, Hybrid-PI controller proposes a new method based self tuning PI controller. Hybrid-PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of induction motor are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.41-44
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• 1988

This paper represents the study of an effective self-tuning PID control for a robot manipulator to track a reference trajectory in spite of the presence of nonlinearities and parameters uncertainties in robot dynamic models. In this control scheme, an error model of the manipulator is established, for the first time, by difference between joint reference trajectory and tracked trajectory. It's model Parameters are estimated by the recursive least-square identification algorithm, and classical controller parameters are determined by pole placement method. A computer simulation study was conducted to demonstrate performance of the proposed self-tuning PID control in joint-based coordinates for a robot with payload.