• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.177-180
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• 2001

This paper describes the calibration method and the evaluation method of relative expanded uncertainty for a multi-axis force/moment sensor. This sensor should be calibrated to be use in the industry. Now, the confidence of the calibration result is expressed with interference error. But it is no inaccurate, because an interference error, besides, a reproducibility error of the sensor, a error of this six-axis force/moment sensor calibrator, and so on. Thus, in order to accurately evaluate the relative expanded uncertainty of it, the concept of the uncertainty should be induced, and these errors must be contained in the relative expanded uncertainty. In this paper, the calibration method is exhibited and the evaluation method of the relative expanded uncertainty is also exhibited. And, a six-axis force/moment sensor was calibrated and the relative expanded uncertainty was evaluated.

• Journal of Power Electronics
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• 제19권4호
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• pp.835-845
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• 2019

This paper presents a robust-optimal control strategy to improve the output-voltage error-tracking and control capability of a DC-DC boost converter. The proposed strategy employs an optimized Fractional-order Proportional-Integral (FoPI) controller that serves to eliminate oscillations, overshoots, undershoots and steady-state fluctuations. In order to significantly improve the error convergence-rate during a transient response, the FoPI controller is augmented with a pre-stage nonlinear error-modulator. The modulator combines the variations in the error and error-derivative via the signed-distance method. Then it feeds the aggregated-signal to a smooth sigmoidal control surface constituting an optimized hyperbolic secant function. The error-derivative is evaluated by measuring the output-capacitor current in order to compensate the hysteresis effect rendered by the parasitic impedances. The resulting modulated-signal is fed to the FoPI controller. The fixed controller parameters are meta-heuristically selected via a Particle-Swarm-Optimization (PSO) algorithm. The proposed control scheme exhibits rapid transits with improved damping in its response which aids in efficiently rejecting external disturbances such as load-transients and input-fluctuations. The superior robustness and time-optimality of the proposed control strategy is validated via experimental results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.896-899
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• 1991

This paper presents the neural network method to predict the Korea composition stock price index. The error back-propagation method is used to train the multi-layer perceptron network. Ten of the various economic indices of the past 7 Nears are used as train data and the monthly transition of the composition stock price index is represented by five output neurons. Test results of this method using the data of the last 18 months are very encouraging.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권6호
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• pp.221-227
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• 2002

In this paper, the system model for the compensation of the low-cost personal navigation system is derived and the error compensation method using GPS is also proposed. WNS(Walking Navigation System) is a kind of personal navigation system using the number of a walk, stride and azimuth. Because the accuracy of these variables determines the navigation performance, computational methods have been investigated. The step is detected using the walking patterns, stride is determined by neural network and azimuth is calculated with gyro output. The neural network filters off unnecessary motions. However, the error compensation method is needed, because the error of navigation information increases with time. In this paper, the accumulated error due to the step detection error, stride error and gyro bias is compensated by the integrating with GPS. Loosely coupled Kalman filter is used for the integration of WNS and GPS. It is shown by simulation that the error is bounded even though GPS signal is blocked.

• 전기학회논문지
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• 제60권11호
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• pp.2064-2075
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• 2011

In this paper, robust multi-level perturbation and observation (MLPO) maximum power point tracking (MPPT) control are presented of the environmental change including the solar radiation and temperature. Because the maximum power point of the Photovoltaic (PV) is changing according to the solar radiation and temperature, the technology which traces the maximum power point in order to increase the power efficiency is recognized as the very important part. The general requirement for the MPPT is that system is simple, the cost is inexpensive, the PV tracking function and output change are small. Conventional perturbation and observation (PO) method is a simple system but there is the disadvantage that an efficiency of system becomes low. In addation, the incremental conductance (IC) control is required expensive CPU because of a large of calculations. In order to solve this problem, in this paper, the MLPO MPPT control using the method diversifying the step size according to the environment condition is presented. The validity of the MLPO method presenting from this paper is proved through analyzing the solar power generation output error at the steady state.

• 한국지능시스템학회논문지
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• 제16권3호
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• pp.297-302
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• 2006

본 논문에서는 지구자계를 이용하여 3축 자계센서의 수직성분자계를 간편하게 보정할 수 있는 방법과 장치를 제안한다. 자계센서의 출력은 설치각도 및 이득오차에 의한 출력 오프셋을 포함하고 있다. 따라서 자계센서를 사용하기에 앞서 보정이 필요하다. 자계센서의 보정은 무자계 공간에서 이루어져야 하나 지구자계를 이용하면 간단하게 자계센서의 출력 오프셋을 보정할 수 있다. 그리고 보정을 위한 장치를 설계하였다. 제안하는 방법과 장치는 실험을 통하여 실용성을 검증하였다.

• Journal of Biosystems Engineering
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• 제20권3호
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• pp.205-216
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• 1995

A fast and inexpensive approximate analysis method to predict power output characteristics of the Stilting engines in a preliminary design stage was investigated. In basic equations proposed by Walker, typical temperatures of working fluids in expansion and compression spaces were treated as those of working fluids in heater and cooler respectively. While the temperature of working fluid in the expansion space was actually lower than that of working fluid in the heater, the temperature of working fluid in the compression space was higher than that of working fluids in the cooler. In this paper, the working fluid temperature of expansion space was treated as lower than the heater temperature and that of compression space was treated as higher than the cooler temperature. Also, according to them, the power output characteristics of the Stirling engine were evaluated with respect to the GPU-3 and 4-215 Stilting engines. The following conclusions were drawn from the analysis. 1. Using the available experimental data from the GPU-3 Stirling engine, it was shown that the approximate analysis predicts the brake power with a maximum error of 19 percent at 1, 000rpm and with a minimum error of 3 percent at 2, 000rpm. 2. The approximate analysis data which for the GPU-3 Stirling engine were much closer to the experimental data than those of adiabatic 2nd order and 3rd order analysis within 1, 500rpm to 2, 500rpm. 3. The approximate analysis data which for the GPU-3 and 4-215 Stilting engines were much closer to the experimental data than those of the Beal number analysis.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.621-623
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• 2000

In this paper, the effective design method of the predictive controller using fuzzy neural networks(FNNs) is presented for the Intelligent control of chaotic nonlinear systems. In our design method of controller, predictor parameters are tuned by the error value between the actual output of a chaotic nonlinear system and that of a fuzzy neural network model. And the parameters of predictive controller using fuzzy neural network are tuned by the gradient descent method which uses control error value between the actual output of a chaotic nonlinear system and the reference signal. In order to evaluate the performance of our controller, it is applied to the Duffing system which are the representative continuous-time chaotic nonlinear systems and the Henon system which are representative discrete-time chaotic nonlinear systems.

• 전기전자학회논문지
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• 제16권1호
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• pp.34-44
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• 2012

본 논문은 스트레인 게이지(strain gauge)식 로드셀(loadcell)의 대표적인 크립오차(creep error)에 대해서 디지털 신호처리방식을 사용한 실용적인 보상법(compensation method)을 제안한다. 신호의 보상방법은 로드셀의 출력응답을 실측해서 보상상수(시정수)와 보상계수를 결정한 후 마이크로프로세서의 내부메모리에 보상상수와 보상계수를 저장한 후 중량값을 디지털로 표시할 시점에 마이크로프로세서에서 연산처리한 크립에러 보상처리값을 로드셀의 출력신호에서 실측한 에러값과 서로 상쇠시키는 보상방법이다. 추가적으로 보상방법을 디지털전자저울에 직접 적용 시험하기 위해서 전용의 보상소프트웨어를 제작한 후 디지털전자저울의 크립특성을 실측해서 보상전 정격출력의 크립오차 0.03%의 로드셀을 정밀디지털전자저울의 허용오차 범위인 0.01%~0.001%이상으로 복잡한 연산처리 없이 정확하게 직접 보상처리하는 실용적인 방법을 제안했다.

• ETRI Journal
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• 제15권2호
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• pp.35-51
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• 1993

This paper presents function approximation based on nonparametric estimation. As an estimation model of function approximation, a three layered network composed of input, hidden and output layers is considered. The input and output layers have linear activation units while the hidden layer has nonlinear activation units or kernel functions which have the characteristics of bounds and locality. Using this type of network, a many-to-one function is synthesized over the domain of the input space by a number of kernel functions. In this network, we have to estimate the necessary number of kernel functions as well as the parameters associated with kernel functions. For this purpose, a new method of parameter estimation in which linear learning rule is applied between hidden and output layers while nonlinear (piecewise-linear) learning rule is applied between input and hidden layers, is considered. The linear learning rule updates the output weights between hidden and output layers based on the Linear Minimization of Mean Square Error (LMMSE) sense in the space of kernel functions while the nonlinear learning rule updates the parameters of kernel functions based on the gradient of the actual output of network with respect to the parameters (especially, the shape) of kernel functions. This approach of parameter adaptation provides near optimal values of the parameters associated with kernel functions in the sense of minimizing mean square error. As a result, the suggested nonparametric estimation provides an efficient way of function approximation from the view point of the number of kernel functions as well as learning speed.