• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.50-50
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• 2000

• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.51-56
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• 2000

This paper presents the characteristics of the dynamic response and calibration technique on a linear variable differential transformer(LVDT). The linear error of the LVDT was proven $\pm$1% in the static calibration and $\pm$0.5% in the dynamic calibration. In this paper, the linearity error generated in the static and dynamic state of the core movement can be eliminated using the correction algorithem of the static and dynamic state derived from the least square linear approximation for the nonlinearity of the curves of direct data fitting and Lagrange polynomials. With the static and dynamic calibration method, the calibration accuracy of the LVDT can be reduced to within $\pm{0.5%.}$.

• 전기학회논문지
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• 제63권8호
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• pp.1075-1079
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• 2014

In this paper, we describe the analysis and the compensation method of the g-sensitivity error for MEMS vibratory gyroscopes. Usually, the g-sensitivity error has been ignored in the commercial MEMS gyroscope, but it deserves our attention to apply for the missile application as a tactical grade performance. Thus, it is necessary to compensate for the g-sensitivity error to reach a tactical grade performance. Generally, the g-sensitivity error seems intuitively to be a gyroscope bias error proportional to the linear acceleration. However, we assert that the g-sensitivity error mainly causes not a bias error but a scale-factor error. And we verify that the g-sensitivity scale-factor error occurs due to the non-linearity of parallel plate electrodes. Therefore, we propose the compensation method to remove the g-sensitivity scale-factor error. The experimental result showed that a proposed compensation method improved successfully the performance of the MEMS vibratory gyroscope.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1999년도 전력전자학술대회 논문집
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• pp.443-447
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• 1999

The AC drive systems of a voltage source inverter and an induction motor. The inverter non linearity caused by the turn on/off time dependency of the current level in the switching IGBT is described in the first part of this paper. To improve the low-speed drive characteristics, accurate applied voltage calculation is proposed under considerations of the compensations for the quantization error in the digital controller, the forward voltage drop of switching drives and the dead time of the inverter. The experimental studies show the improved drive characteristics.

• Smart Structures and Systems
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• 제32권2호
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• pp.101-109
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• 2023

In order to improve the measurement accuracy of the 6-dimensional accelerometer, the cross coupling compensation method of the accelerometer needs to be studied. In this paper, the non-linear error caused by cross coupling of piezoelectric six-dimensional accelerometer is compensated online. The cross coupling filter is obtained by analyzing the cross coupling principle of a piezoelectric six-dimensional accelerometer. Linear and non-linear fitting methods are designed. A two-level calibration hybrid compensation algorithm is proposed. An experimental prototype of a piezoelectric six-dimensional accelerometer is fabricated. Calibration and test experiments of accelerometer were carried out. The measured results show that the average non-linearity of the proposed algorithm is 2.2628% lower than that of the least square method, the solution time is 0.019382 seconds, and the proposed algorithm can realize the real-time measurement in six dimensions while improving the measurement accuracy. The proposed algorithm combines real-time and high precision. The research results provide theoretical and technical support for the calibration method and online compensation technology of the 6-dimensional accelerometer.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.2142-2153
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• 2014

Linearization of transducer characteristic plays a vital role in electronic instrumentation because all transducers have outputs nonlinearly related to the physical variables they sense. If the transducer output is nonlinear, it will produce a whole assortment of problems. Transducers rarely possess a perfectly linear transfer characteristic, but always have some degree of non-linearity over their range of operation. Attempts have been made by many researchers to increase the range of linearity of transducers. This paper presents a method to compensate nonlinearity of Linear Variable Displacement Transducer (LVDT) based on Extreme Learning Machine (ELM) method, Differential Evolution (DE) algorithm and Artificial Neural Network (ANN) trained by Genetic Algorithm (GA). Because of the mechanism structure, LVDT often exhibit inherent nonlinear input-output characteristics. The best approximation capability of optimized ANN technique is beneficial to this. The use of this proposed method is demonstrated through computer simulation with the experimental data of two different LVDTs. The results reveal that the proposed method compensated the presence of nonlinearity in the displacement transducer with very low training time, lowest Mean Square Error (MSE) value and better linearity. This research work involves less computational complexity and it behaves a good performance for nonlinearity compensation for LVDT and has good application prospect.

• 센서학회지
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• 제4권1호
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• pp.21-28
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• 1995

$1000^{\circ}C$까지 비직선 특성을 보상할 수 있는 휴대용 K형 열전대 온도계를 설계 및 제작하였다. 열전대를 이용한 온도계에서 해결해야 할 문제는 비선형특성 보상과 기준점 보상이다. 열전대의 비선형특성은 EPROM을 사용하여 보상하였으며, 기준점 보상은 집적 소자 AD595A를 사용하여 수행하였다. 비선형 특성을 보상하기 전에는 $876^{\circ}C$에서 최대 $23.6^{\circ}C$(2.69%)의 오차가 있었으나, 제작된 휴대용 K형 열전대 온도계로 측정한 결과는 전체 온도 범위 내에서 ${\pm}2^{\circ}C$(0.2%)의 오차 특성을 가진다. 이런 특성은 K형 열전대를 사용하여 측정할 수 있는 상용한도 $1000^{\circ}C$ 범위에서 온도센서의 정밀도 규격을 만족한다. 그러므로 제작된 휴대용 K형 열전대 온도계는 넓은 온도 측정에 비교적 정확하게 사용할 수 있다. 그리고 이러한 비선형 특성을 보상하는 기법은 다른 종류의 온도센서의 보상에 적용할 수 있다.

• Journal of the Optical Society of Korea
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• 제3권2호
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• pp.35-40
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• 1999

One of main error sources in white light scanning interferometry is the inaccuracy of scanning mechanisms in that PZT(piezoelectric transducer) micro-actuators are preferably used. We propose a new calibration method that is capable of identifying actual scanning errors directly by analyzing the spectral distribution of sampled interferograms. This calibration provides an effective means of self-compensation for the non-linearity errors caused by PZT hysteresis, enhancing the measurement uncertainty to a level of 5 nanometers over an entire measuring range of 100 ${\mu}{\textrm}{m}$.

• 제어로봇시스템학회논문지
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• 제22권6호
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• pp.389-396
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• 2016

The sealing robot must be able to calculate the slope of a contact surface for complete adherence of the sealing on different concrete shapes. After the slope is obtained, the robot will track on the surface of the concrete, but this process contains an error in the actual purpose of the force command. The reason this a phenomenon occurs, the non-linearity of the contact surface and the end-effector, is due to parasitic coupling. Errors like make it difficult to measure accurately the respective factors. Therefore, it is regarded as a disturbance that occurs when it follows the work surface it. In this paper, we selected the friction coefficient of the surface as a control factor and designed a compensator to reduce effects of disturbance. Finally, in view of the non-linearity of the end-effector of a robot to contact surfaces directly, we propose a robust force tracking controller in the finite range for managing disturbances that occur during the sealing.

• 전기학회논문지
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• 제58권1호
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• pp.173-180
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• 2009

It is difficult to predict non-stationary or chaotic time series which includes the drift and/or the non-linearity as well as uncertainty. To solve it, we propose an effective prediction method which adopts data preprocessing and multiple model TS fuzzy predictors combined with model selection mechanism. In data preprocessing procedure, the candidates of the optimal difference interval are determined based on the correlation analysis, and corresponding difference data sets are generated in order to use them as predictor input instead of the original ones because the difference data can stabilize the statistical characteristics of those time series and better reveals their implicit properties. Then, TS fuzzy predictors are constructed for multiple model bank, where k-means clustering algorithm is used for fuzzy partition of input space, and the least squares method is applied to parameter identification of fuzzy rules. Among the predictors in the model bank, the one which best minimizes the performance index is selected, and it is used for prediction thereafter. Finally, the error compensation procedure based on correlation analysis is added to improve the prediction accuracy. Some computer simulations are performed to verify the effectiveness of the proposed method.