• Journal of the Semiconductor & Display Technology
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• v.19 no.1
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• pp.17-22
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• 2020

Recently, the decrease in thin film thickness has been actively studied by changing several physical elements such as the increase in revolution velocity of lower substrate equipped with AC or DC motor. In this paper, we propose a novel spin coater control system that changes AC or DC motor and common use software with limitation of velocity and position control into step motor and LABVIEW software based on GUI to control revolution velocity and position more precisely. By determining six input values of rotation velocity 1, 5, 10, 25, 50, 100 PPS, we fabricated six samples using coating target, TA(tantalum) on silicon substrate and measured their thin film thickness by SEM. Hence, this research can be applied to inferring thin film thickness of tantalum regarding any value of revolution velocity without additional experiments and for linear reference model via property analysis of thin film thickness using other thin-film materials.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.61-70
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• 2000

An Adaptive Positive Position Feedback method is presented for controlling the roll of the supersonic smart projectile. The proposed strategy combines the attractive attributes of Positive Position Feedback(PPF) of Goh and Caughey, and Lyapunov stability theorem. The parameters of Adaptive-PFF controller are adjusted in an adaptive mauler in order to follow the performance of an optimal reference model. In this way, optimal damping and zero steady-state errors can be achieved even in the presence of uncertain or changing plant parameters. The performance obtained with the Adaptive-PPF algorithm is compared with conventional PPF control algorithm. The results obtained emphasize the potential of Adaptive-PPF algorithm as an efficient means for controlling plants such as supersonic flight systems with uncertainties in real time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.794-803
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• 2016

This paper propose a sensorless control system of IPMSM with a adaptive back-EMF estimator and improved instantaneous reactive power compensator. A saliency-based back-EMF is estimated by using the adaptive algorithm. The estimated back-EMF is inputted to the phase locked loop(PLL) and the improved instantaneous reactive power(IRP) compensator for estimating the position/speed of the rotor and compensating the error components between the estimated and the actual position, respectively. The stability of the proposed system is achieved through Popov's hyper stability criteria. The validity of proposed algorithm is verified by the simulations and experiments.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.2
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• pp.27-32
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• 2015

A maximum power point tracking (MPPT) algorithm using fuzzy controller was considered. MPPT method was implemented based on the voltage and reference PV voltage value was obtained from Artificial Neural Network (ANN)-model of PV modules. Therefore, measuring only the PV module voltage is adequate for MPPT operation. Fuzzy controller is used to directly control dc-dc buck converter. The simulation results have been used to verify the effectiveness of the algorithm. The proposed method is compared with conventional PO(perturbation & observation), IC(Incremental Conductance) method. The nonlinearity and adaptiveness of fuzzy controller provided good performance under parameter variations such as solar irradiation.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.241-248
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• 2007

The accuracy of all the schemes that belong to vector controlled induction machine drives is strongly affected by parameter variations. The aim of this paper is to examine iron losses and magnetic saturation effect in sensorless vector control of induction machines. At first, an approach to induction machine modelling and vector control scheme, which account for both iron loss and saturation, is presented. Then, a model reference adaptive system (MRAS) based speed estimator is developed. The speed estimation is modified in such a way that iron losses and the variation in the saturation level are compensated. Thus by substituting an artificial neural network flux estimator into the MRAS speed estimator. Experimental results are presented to verify the effectiveness of the proposed approach.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.11
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• pp.1069-1076
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• 2007

This paper presents the road simulator control technology for reproducing the road input signal to implement the real road data. The simulator consists of the hydraulic pump, servo valve, hydraulic actuator and its control equipment. The QFT(Quantitative Feedback Theory) is utilized to control the simulator effectively. The control system illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) for a parametric uncertain model. A force controller is designed to communicate the control signal between simulator and digital controller. Tracking specification is satisfied with upper and lower bound tolerances on the steep response of the system to the reference signal. The efficacy of the QFT force controller is verified through the numerical simulation, in which combined dynamics and actuation of the hydraulic servo system are tested. The simulation results show that the proposed control technique works well under uncertain hydraulic plant system. The conventional software (Labview) is used to make up for the real controller in the real-time basis, and the experimental works show that the proposed algorithm works well for a single road simulator.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.1
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• pp.18-30
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• 2016

In this paper, we propose a new technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.

• Journal of Power Electronics
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• v.11 no.5
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• pp.743-750
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• 2011

This article deals with the sensor-less control of a DC Motor via a SEPIC Converter-Full Bridge combination powered through solar panels. We simultaneously regulate, both, the output voltage of the SEPIC-converter to a value larger than the solar panel output voltage, and the shaft angular velocity, in any of the turning senses, so that it tracks a pre-specified constant reference. The main result of our proposed control scheme is an efficient linear controller obtained via Lyapunov. This controller is based on measurements of the converter currents and voltages, and the DC motor armature current. The control law is derived using an exact stabilization error dynamics model, from which a static linear passive feedback control law is derived. All values of the constant references are parameterized in terms of the equilibrium point of the multivariable system: the SEPIC converter desired output voltage, the solar panel output voltage at its Maximun Power Point (MPP), and the DC motor desired constant angular velocity. The switched control realization of the designed average continuous feedback control law is accomplished by means of a, discrete-valued, Pulse Width Modulation (PWM). Experimental results are presented demonstrating the viability of our proposal.

• The Journal of Korean Academy of Prosthodontics
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• v.57 no.2
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• pp.102-109
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• 2019

Purpose: The purpose of this study was to evaluate the accuracy of three types of intraoral scanners and the accuracy of the single abutment and bridge abutment model. Materials and methods: In this study, a single abutment, and a bridge abutment with missing first molar was fabricated and set as the reference model. The reference model was scanned with an industrial three-dimensional scanner and set as reference scan data. The reference model was scanned five times using the three intraoral scanners (CS3600, CS3500, and EZIS PO). This was set as the evaluation scan data. In the three-dimensional analysis (Geomagic control X), the divided abutment region was selected and analyzed to verify the scan accuracy of the abutment. Statistical analysis was performed using SPSS software (${\alpha}=.05$). The accuracy of intraoral scanners was compared using the Kruskal-Wallis test and post-test was performed using the Pairwise test. The accuracy difference between the single abutment model and the bridge abutment model was analyzed by the Mann-Whitney U test. Results: The accuracy according to the intraoral scanner was significantly different (P < .05). The trueness of the single abutment model and the bridge abutment model showed a statistically significant difference and showed better trueness in the single abutment (P < .05). There was no significant difference in the precision (P = .616). Conclusion: As a result of comparing the accuracy of single and bridge abutments, the error of abutment scan increased with increasing scan area, and the accuracy of bridge abutment model was clinically acceptable in three types of intraoral scanners.