• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.541-543
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• 1998

Generally, PI control is simple and easy to implement and gains of PI control are determined by specifying a dynamics of the servo driver system. However, the gain-tuning is so difficult that it is relied on an expert's effort. This paper presents a gain auto-tuning method for PI controllers based on a fuzzy inference mechanism. First, the proposed fuzzy inference system identifies a system moment of inertia and adjusts control gains by using the difference in speed responses between a real plant and a reference model. Second, this paper proposes an improved fuzzy PI controller. To reduce the speed overshoot, we adapt a control method that selects a proper PI gains with respect to the load inertia variation. To prove the validity of the proposed gain tuning algorithm and the feasibility of the servo drive, a high performance servo drive will be implemented by DSP(TMS320C31) and intelligent power module (IPM). The proposed controller is applied to the speed control of the 300W AC servo motor. Some simulations and experimental results show that the proposed fuzzy PI controller is more robust than the conventional PI controller against the load inertia variation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.52-61
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• 2012

The design method for cumulative sum (CUSUM) control charts, which can be robust to autoregressive moving average (ARMA) modeling errors, has not been frequently proposed so far. This is because the CUSUM statistic involves a maximum function, which is intractable in mathematical derivations, and thus any modification on the statistic can not be favorably made. We propose residual-based robust CUSUM control charts for monitoring autocorrelated processes. In order to incorporate the effects of ARMA modeling errors into the design method, we modify parameters (reference value and decision interval) of CUSUM control charts using the approximate expected variance of residuals generated in model uncertainty, rather than directly modify the form of the CUSUM statistic. The expected variance of residuals is derived using a second-order Taylor approximation and the general form is represented using the order of ARMA models with the sample size for ARMA modeling. Based on the Monte carlo simulation, we demonstrate that the proposed method can be effectively used for statistical process control (SPC) charts, which are robust to ARMA modeling errors.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.6
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• pp.96-103
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• 2006

An MRAC-based adaptive current control scheme of an AC servo motor is presented for the performance improvement of a servo drive. Although the predictive current control is known to give ideal transient and steady-state responses, its steady-state response my be degraded under motor parameter variations. To overcome such a limitation, the disturbances caused by the parameter variations will be estimated by using an MRAC technique and compensated by a feedforward control. The proposed scheme does not require the measurement of the phase voltage unlike the conventional disturbance estimation scheme using observer. The asymptotic stability is proved. The proposed scheme is implemented using DSP TMS320C31 and the effectiveness is verified through the comparative simulations and experiments.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.3
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• pp.216-222
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• 2017

The rotor position of a PM synchronous motor is commonly estimated from the mathematical model for the sensorless control without rotor position sensors. For the magnet flux-based rotor position estimator in the stationary reference frame, the magnet flux estimator for estimating rotor position and speed includes the integrator. The integrator in the magnet flux estimator may accumulate the offset of the current sensors and the voltage drift. This continuous accumulation of the offset may cause the drift and overflow in the integrator, such that the estimated rotor position and speed may fail to track the real rotor position and speed. In this paper, the magnet flux estimator without integrator is proposed to avoid overflow in the integrator. The proposed rotor position and speed estimator based on magnet flux estimator are verified through simulation and experiment.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.339-346
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• 2022

To operate in real environment, humanoid robots should be able to react to unknown disturbances. To deal with disturbances, various robust control algorithms have been developed for decades. But for collaborative works such as teleoperation system, a compliance control can be the better solution for disturbance reactions. In this paper, a center of mass (CoM) compliance control algorithm for humanoid robots is proposed. The proposed algorithm is based on the state observer and positive feedback of disturbance. With the state observer based on humanoid CoM control performance model, disturbance in each direction can be observed. The positive feedback of disturbances to the reference CoM trajectory enables compliant motion. The main contributions of this algorithm are achieving compliance independently in each axis and maintaining balance against external force. Through dynamic simulations, the performance of the proposed method was demonstrated. Under two types of disturbance conditions, humanoid robot DYROS-JET reacted with compliant motion via the proposed algorithm.

• Research in Community and Public Health Nursing
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• v.11 no.2
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• pp.333-346
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• 2000

The purpose of this study was designed to test and develope the structural model that explains health promoting behaviors among college students in Korea. The hypothetical model was constructed on the Pender's Health promotion Model(l996) and the inclusion of some influential factors for life satisfaction. The conceptual framework was built around eight constructs. Exogenous variables included in the model were self-esteem, perceived health status, self-efficacy, internal locus of control, chance locus of control. powerful other locus of control. Endogenous variables were health promotion behaviors and life satisfaction. The results are as follows; 1. The overall fit of the hypothetical model to the data was moderate <$x^2$=4.18(df=11. p=0.041), GFI= 0.99, AGFI= 0.76, RMR= 0.019, CFI= 0.99, CN= 248.50> 2. Path and variable of the model were modified by considering both its theoretical implication and statistical significance of parameter estimates. Compared to the hypothetical model. the revised model has become parsimonious and had a better fit to the data expected in a chi-square value <$x^2$=8.43( df= 16, p=0.21), GFI= 0.99, AGFI= 0.92., RMR= 0.024, CFI= 0.99, CN= 312.01> 3. Some of the predictive factors. especially self efficacy. self esteem. powerful others locus of control. perceived health status revealed the direct effects on health promoting behaviors. Of these variables. self-efficacy was the most signigicant factor. These predictive variables of health promoting behaviors explained 59% of total variances in the model. 4. Health promoting behaviors, self-esteem. and perceived health status revealed direct effect on the life satisfaction. Self-efficacy was identified as an important variable that contributed indirectly to improve life satisfaction by enhancing health promoting behaviors. These predictive variables of life satisfaction explained 42% of total variances in the model. In conclusion. the derived model in this study is considered appropriate in explaining and predicting health promoting models and life satisfaction among college students in Korea and could effectively be used as a reference model for further studies by suggesting a direction in health promoting nursing practices.

• Smart Media Journal
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• v.10 no.1
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• pp.79-87
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• 2021

In recent years research on automatic font generation with machine learning mainly focus on using transformation-based methods, in comparison, generative model-based methods of font generation have received less attention. Transformation-based methods learn a mapping of the transformations from an existing input to a target. This makes them ambiguous because in some cases a single input reference may correspond to multiple possible outputs. In this work, we focus on font generation using the generative model-based methods which learn the buildup of the characters from noise-to-image. We propose a novel way to train a conditional generative deep neural model so that we can achieve font style control on the generated font images. Our research demonstrates how to generate new font images conditioned on both character class labels and character style labels when using the generative model-based methods. We achieve this by introducing a modified generator network which is given inputs noise, character class, and style, which help us to calculate losses separately for the character class labels and character style labels. We show that adding the character style vector on top of the character class vector separately gives the model rich information about the font and enables us to explicitly specify not only the character class but also the character style that we want the model to generate.

• Toxicological Research
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• v.34 no.3
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• pp.191-197
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• 2018

In 2015, a candidate for the second national reference standard (NRS) of Gloydius snake venom was produced to replace the first NRS of Gloydius snake venom. In the present study, the potencies of the candidate were determined by a collaborative study, and the qualification of the candidate was estimated. The potencies of the candidate were determined by measuring the murine lethal titers and lapine hemorrhagic titers of venom against the regional working reference standard (RWRS) for antivenom using the methods described in the previous report for the first NRS of Gloydius snake venom. Three Korean facilities contributed data from a total of 30 independent assays. Subsequently, two foreign national control research laboratories contributed to this collaborative study. The results were calculated using the Reed-Muench method for lethality and determined using a mixed-effects model for hemorrhage. The general common potencies of the lethal and hemorrhagic titers were obtained from the results of the 30 tests performed at three Korean facilities. The results are expressed in micrograms for 1 test dose (TD) with a 95% confidence interval as follows: a lethal titer of $90.13{\mu}g/TD$ (95% confidence interval = $87.39{\sim}92.86{\mu}g$) and a hemorrhagic titer of $10.80{\mu}g/TD$ (95% confidence interval = $10.46{\sim}11.14{\mu}g$). In addition, the candidate preparation showed good quality evaluation according to the results of the quality estimation of the candidate and is judged to be suitable to serve as the Korean NRS for snake venom. In conclusion, the second NRS of Gloydius snake venom was established in this study and will be used for national quality control, including a national lot release test of Korean antivenom products.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.643-651
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• 2007

The various blood pressure simulators have been proposed to evaluate and improve the performance of the automatic sphygmomanometer. These have some problems such as the deviation of the actual blood pressure waveform, limitation in the blood pressure condition of the simulator, or difficulty in displaying the blood flow. An improved simulator using disturbance observer is proposed to supplement the current problems of the blood pressure simulator. The proposed simulator has an artificial arm model capable of feeding appropriate fluids that can generate the blood pressure waveform to evaluate the automatic sphygmomanometer. A controller was designed and thereafter, simulation was performed to control the output signal with respect to the reference input in the fluid dynamic model using the proposed proportional control valve. To minimize the external fluctuation of pressure applied to the artificial arm, a disturbance observer was designed on the plant. A hybrid controller combined with a proportional controller and feed-forward controller was fabricated after applying a disturbance observer to the control plant. Comparison of the simulations between the conventional proportional controller and the proposed hybrid controller indicated that even though the former showed good control performance without disturbance, it was affected by the disturbance signal induced by the cuff. The latter exhibited an excellent performance under both situations.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.2
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• pp.107-114
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• 2014

This paper proposes a common rail pressure control algorithm for passenger car diesel engines. For handling the parameter-varying characteristics of common rail systems, the quantitative feedback theory (QFT) is applied to the design of a robust rail pressure control algorithm. The driving current of the pressure control valve and the common rail pressure are used as the input/output variables for the common rail system model. The model parameter uncertainty ranges are identified through experiments. Rail pressure controller requirements in terms of tracking performance, robust stability, and disturbance rejection are defined on a Nichols chart, and these requirements are fulfilled by designing a compensator and a prefilter in the QFT framework. The proposed common rail pressure control algorithm is validated through engine experiments. The experimental results show that the proposed rail pressure controller has a good degree of consistency under various operating conditions, and it successfully satisfies the requirements for reference tracking and disturbance rejection.