• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.271-272
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• 2006

This paper presented a new experimental gain tuning technique for a Multi-Axis Servo System. First, the investigation for proportional gain of velocity control loop by using a Dynamic Signal Analyzer (DSA) was performed. Using the FUNCTION characteristic of DSA based on the Bode plot, the Bode plot of open loop transfer function was obtained. In turn, the integral gain of a servo controller can be found out by using the Integration time constant extracted from the Bode plot of open loop transfer function. In the meanwhile, the positional gain of the servo controller has been obtained by using the Bode plot of the closed loop transfer function. We have also proposed the technique to find out an optimal parameter of a notch filter, which has a great influence on vibration reduction, by using the damping factor extracted from the Bode plot of closed loop transfer function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.213-217
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• 2008

In this paper, a new design method for IMC-PID that adds a phase scaling factor of system identifications to the standard IMC-PID controller as a control parameter is proposed. Based on analytically derived frequency properties such as gain, phase margin and maximum magnitude of sensitivity function, this tuning rule is an optimal control method determining the optimum values of controlling factors to minimize the cost function, integral error criterion of the step response in time domain, in the constraints of design parameters to guarantee qualified frequency design specifications. The proposed controller improves existing single-parameter design methods of IMC-PID in the inflexibility problem to be able to consider various design specifications. Its effectiveness is examined by a simulation example, where a comparison of the performances obtained with the proposed tuning rule and with other common tuning rules is shown.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1857-1862
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• 2008

Resonant frequency tuning of micro devices is essential to achieve performance uniformity and high sensitivity. Previously reported frequency tuning methods using electrostatic force or mass deposition are not directly applicable to non-conducting polymer devices and have limitations such as dielectric breakdown or low tunable bandwidth. In this paper, thermally frequency-tunable microactuators with poly-dimethylsiloxane membranes are proposed. Permanent and/or nonpermanent frequency tunings are possible using a simple temperature control of the device. Resonant frequency and Q-factor variations of devices according to temperature change were studied using a micro heater and laser Doppler vibrometer. The initial resonant frequencies determined by polymer curing and hardening temperatures are reversibly tuned by thermal cycles. The measured resonant frequency of 9.7 kHz was tuned up by ${\sim}25%$ and Q-factor was increased from 14.5 to 27 as the micro heater voltage increased from 0 to 70 V.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1225-1235
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• 2011

This paper suggests a method for tuning a numerically simulated wind speed data, provided by NIMR(National Institute of Meteorological Research) and generated from a numerical meteorological model to improve a wind resource map with a $1Km{\times}1Km$ resolution. To this end, "tuning factor method" is developed that consists of two procedures. First, estimate monthly wind fields based on a suitably designed statistical wind field model that covers 345,682 regions obtained by $1Km{\times}1Km$ lattice sites in South Korea. The second procedure computes the tuning factor and then tunes the generated wind speeds of each month as well as each lattice site. The second procedure is based on the wind fields estimated by the first procedure. The performance of the suggested tuning method is demonstrated by using two wind data(both TMY and numerically simulated wind speed data) of 75 weather station areas.

• Journal of Information Technology Services
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• v.19 no.5
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• pp.83-91
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• 2020

Language Models such as BERT has been an important factor of deep learning-based natural language processing. Pre-training the transformer-based language models would be computationally expensive since they are consist of deep and broad architecture and layers using an attention mechanism and also require huge amount of data to train. Hence, it became mandatory to do fine-tuning large pre-trained language models which are trained by Google or some companies can afford the resources and cost. There are various techniques for fine tuning the language models and this paper examines three techniques, which are data augmentation, tuning the hyper paramters and partly re-constructing the neural networks. For data augmentation, we use no-answer augmentation and back-translation method. Also, some useful combinations of hyper parameters are observed by conducting a number of experiments. Finally, we have GRU, LSTM networks to boost our model performance with adding those networks to BERT pre-trained model. We do fine-tuning the pre-trained korean-based language model through the methods mentioned above and push the F1 score from baseline up to 89.66. Moreover, some failure attempts give us important lessons and tell us the further direction in a good way.

• Journal of the Korean Society of Industry Convergence
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• v.3 no.1
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• pp.3-8
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• 2000

This paper describes a development of self tuning scheme for PI and PO type fuzzy controllers. The output scaling factor(SF) is adjusted on-line by fuzzy rules according to the current trend of the controlled process. The rule-base for tuning the output SF is defined on error and change of error for the controlled variable using the most natural and unbiased membership functions. Simulation results demonstrate the better control performance can be achieved in comparison with Ziegler-Nichols(Z-N) PID controllers.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.514-520
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• 2010

This paper is about control algorithms that bi-direction DC-DC Converter using Super Capacitor and regenerative power from DC feeding system in train. In order to take advantage of regenerative energy efficient, charge and discharge level value of energy storage system serve as an important factor. Respect to output fluctuations of the substation and catenary voltage changing, we offers Charge-Discharge Auto Level Tuning Algorithms to improve system following of Energy Storage System.

• 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.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.338-341
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• 1994

This paper presents a Fuzzy-PID controller based on Fuzzy logic. Up to now PID controller has had the difficulty of obtaining the optimal gain, and Fuzzy controller has had the difficulty of determining scale factor affecting the performance of control. So that a Fuzzy-PID controller is presented here self tuning of the scale factor and optimal gain. The results of simulation show a good performance in comparison with Ziegler-Nichols controller, having the generality of determining the components of scale factor in Fuzzy rule.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.265-271
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• 1992

It is the purpose of this paper to present a dialogical designing method for control system using a rough grasp of the unknown process property. We deal with a single-input single-output feedback control system with a fuzzy controller. The process property is roughly estimated by the step response, and the fuzzy controller is interactively modified according to the operator's requests. The modifying rules mainly derived from computer simulation are useful for almost every process, such as an unstable process and a non-minimum phase process. The fuzzy controller is tuned by taking notice of four characteristics of the step response: (1) rising time, (2) overshoot, (3) amplitude and (4) period of vibration. The tuning position of the controller is fourfold: (1) antecedent gain factor GE or GCE, (2) consequent gain factor GDU, (3) arrangement of the antecedent fuzzy labels and (4) arrangement of the control rules. The rules give an instance to the respective items of the controller in an effective order. The modified fuzzy PI controller realizes a good response of a stable process. However, because the GDU tuning becomes difficult for the unstable process, it is necessary to evaluate the stability of the process from the initial step response. The fuzzy PI controller is applied to the process whose initial step response converges with GDU tuning. The fuzzy PI controller with modified sampling time is applied to the process whose step response converges under the repeated application of the GDU tuning. The fuzzy PD controller is applied to the process whose step response never converges by the GDU tuning.