• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.226-231
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• 2016

Researching and developing mobile robot are quite important. Autonomous driving of mobile robot is important in various working environment. For its autonomous driving, mobile robot detects obstacles and avoids them. Purpose of this thesis is to analyze kinematics model of the mobile robot and show the efficiency of type-2 fuzzy self-tuning PID controller used for controling steering angle. Type-2 fuzzy is more flexible in verbal expression than type-1 fuzzy because it has multiple values unlike previous one. To compare these two controllers, this paper conduct a simulation by using MATLAB Simulink. The result shows the capability of type-2 fuzzy self-tuning PID is effective.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1769-1776
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• 2022

Automatically summarizing long sentences is an important technique. The BART model is one of the widely used models in the summarization task. In general, in order to generate a summarization model of a specific domain, fine-tuning is performed by re-training a language model trained on a large dataset to fit the domain. The fine-tuning is usually done by changing the number of nodes in the last fully connected layer. However, in this paper, we propose a fine-tuning method by adding an attention layer, which has been recently applied to various models and shows good performance. In order to evaluate the performance of the proposed method, various experiments were conducted, such as accumulating layers deeper, fine-tuning without skip connections during the fine tuning process, and so on. As a result, the BART model using two attention layers with skip connection shows the best score.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.9 s.351
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• pp.10-16
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• 2006

This paper presents a fast switching CMOS frequency synthesizer with a new coarse tuning scheme for PHS applications. The proposed coarse tuning method selects the optimal tuning capacitances of the LC-VCO to optimize the phase noise and the lock-time. The measured lock-time is about $20{\mu}s$ and the phase noise is -121dBc/Hz at 600kHz offset. This chip is fabricated with $0.25{\mu}m$ CMOS technology, and the die area is $0.7mm{\times}2.1mm$. The power consumption is 54mW at 2.7V supply voltage.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.22-33
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• 1999

This paper presents the method for the automatic tuning of a design weighting polynomial parameters of a generalized minimum-variance stochastic ultivariable self-tuning controller which adapts to changes in the higher order nonminimum phase 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 the design weighting polynomial parameters of the controller. The proposed multivariable self-tuning method is simple and effective compared with pole restriction method. The computer simulation results are presented to adapt the higher order multivariable system with nonminimum phase and with changeable system parameters.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1297-1302
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• 2014

This paper presents modern optimization methods for determining the optimal parameters of proportional-integral-derivative (PID) controller for coupled tank systems. The main objective is to obtain a fast and stable control system for coupled tank systems by tuning of the PID controller using the Particle Swarm Optimization algorithm. The result is compared in terms of system transient characteristics in time domain. The obtained results using the Particle Swarm Optimization algorithm are also compared to conventional PID tuning method like the Ziegler-Nichols tuning method, the Cohen-Coon method and IMC (Internal Model Control). The simulation results have been simulated by MATLAB and show that tuning the PID controller using the Particle Swarm Optimization (PSO) algorithm provides a fast and stable control system with low overshoot, fast rise time and settling time.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.6
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• pp.797-803
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• 2010

A method has been developed to tune the static stiffness at a rotation joint considering the whole machine tool system by interactive use of finite element method and experiment. This paper describes the procedure of this method and shows the results. The method uses the static experiment on measurement model which is set-up so that the effects of uncertain factors can be excluded. For FEM simulation, the rotation joint model is simplified using only spindle, bearing and spring. At the rotation joint, the damping coefficient is ignored, The spindle and bearing is connected by only spring. By static experiment, 500 N is forced to the front and behind portion of spindle and the deformation is measured by capacitive sensor. The deformation by FEM simulation is extracted with changing the static stiffness from the initial static stiffness considering only rotation joint. The tuning static stiffness is obtained by exploring the static stiffness directly trusting the deformation from the static experiment. Finally, the general tuning method of the static stiffness of machine tool joint is proposed using the force stream and the modal analysis of machine tool.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.875-882
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• 2023

In this paper, we propose a virtual tuning technique for a temperature controller using the PID algorithm. Virtual simulation on a computer was used using the mathematical expression of the control object. A technique for accurately calculating the gain of the PID algorithm was introduced through detailed computer data analysis, and superior performance compared to conventional experimental tuning results was verified. In addition, it has the advantage of replacing tuning experiments conducted on actual control subjects, so there are no temporal or spatial limitations. Tuning experiments that actually operate the control object do not show detailed data that appears during the process. The accuracy of the experiment could not be guaranteed, and the results could not be confirmed immediately. Through the proposed technique, the entire tuning process can be accurately checked on a computer and the cause of problems that occur can also be analyzed.

• Korean Journal of Optics and Photonics
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• v.12 no.4
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• pp.257-262
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• 2001

A Littman type tunable external-cavity diode laser system was developed. The laser output which is the Oth-order diffracted beam from a diffraction grating in an external cavity is a single longitudinal mode. Its FWHM was measured as less than 9 MHz. With the diode driving current of 140 mA and operating temperature of $25^{\circ}C$, the coarse tuning range of 3.475 urn was measured. A fine tuning experiment in which an external mirror was rotated by a PZT driven by a sawtooth wave was performed, and its tuning range of 0.042 urn was measured. sured.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.221-229
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• 2022

Sliding mode control (SMC) is a robust control method to control a robot arm with nonlinear properties. A high switching gain of SMC causes chattering problems, although the SMC allows the adequate control performance by giving high switching gain, without the exact robot model containing nonlinear and uncertainty terms. In order to solve this problem, SMC with sliding perturbation observer (SMCSPO) has been researched, where the method can reduce the chattering by compensating the perturbation, which is estimated by the observer, and then choosing a lower switching control gain of SMC. However, optimal gain tuning is necessary to get a better tracking performance and reducing a chattering. This paper proposes a method that the Q-learning automatically tunes the control gains of SMCSPO with an iterative operation. In this tuning method, the rewards of reinforcement learning (RL) are set minus tracking errors of states, and the action of RL is a change of control gain to maximize rewards whenever the iteration number of movements increases. The simple motion test for a 7-DOF robot arm was simulated in MATLAB program to prove this RL tuning algorithm. The simulation showed that this method can automatically tune the control gains for SMCSPO.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.3
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• pp.367-376
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• 2012

This paper describes a Adaptive Impedance Tuning Circuit which can be adaptively tuned between circuit's characteristic impedance and the arbitrary load impedance. The Adaptive Impedance Tuning Circuit is consisted of such parts as mismatch sensor, impedance tuner and tuning algorithm. Each parts's design methods proposed in other papers are compared with their advantages and disadvantages. And we propose simple design method for Adaptive Impedance Tuning Circuit using a ${\lambda}/4$ transmission line and ${\pi}$-network. Calculation formulas and selection algorithm from calculated values of a complex load impedance are proposed and simulation using induced calculation formulas and selection algorithm is performed. Simulation results show good agreement with theoretical predictions.