• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.229-233
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• 2009

This paper proposes a correction method for the error inherently created by time-step approximation in finite element analysis (FEA). For a simple RL and RLC linear circuit, the error in time-step analysis is analytically investigated, and a correction method is proposed for a non-linear system as well as a linear one. Then, for a practical inductor model, linear and non-linear time-step analyses are performed and the calculation results are corrected by the proposed methods. The accuracy of the corrected results is confirmed by comparing the electric input and output powers.

• Progress in Medical Physics
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• v.1 no.1
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• pp.61-68
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• 1990

We have designed the calculation model(AMC method) of electron output for the cut-out fieldsand studied the influence of shielding block size. The output of electron was measured in the water phantom at dmax, for 20 $\times$ 20cm$^2$ cone size electron beams from CL/1800 linear accelerator(Varian, USA), Which generates the energy of 6, 9, 12, 15 and 18MeV electron beams. The shielding blocks were rectangular or squre shaped, low melting point alloy. We can predict the output from the arbitrarily rectangular shaped block within 1% error. by using the AMC method, which considers the contribution of the collimator(block) scatter and the phantom scatter.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.1
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• pp.89-96
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• 2022

In this paper, to evaluate the output quality of the cementitious composite mixture for printing with the ME method for construction 3D printer, visual inspection of the output appearance and the dimensional error rate, compressive strength and flexural strength of the output were measured. As a result of the test, the mixing design with excellent output appearance was P1-2, P1-4, P2-5, P2-6, and the mixing design with good output appearance was P0-1, P1-1, P1-3, P1-6, P1-7 and P2-4. Of these mixing designs, P0-1 and P2-6 had the lowest dimensional error rates As a result of evaluating the compressive strength and flexural strength of the various mixing designs, the Mixing design with excellent output designs showed good mechnical properties. However, mixing designs with excellent mechanical properties does not necessarily have excellent output quality. Therefore, in order to accurately evaluate the output quality, it is judged that visual inspection and dimensional error rate inspection should be performed first, and then the mechanical characteristics should be reviewed.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.453-459
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• 2008

The neural network is currently being used throughout numerous control system fields. However, it is not easy to obtain an input-output pattern when the neural network is used for the system of a single feedback controller and it is difficult to obtain satisfactory performance with when the load changes rapidly or disturbance is applied. To resolve these problems, this paper proposes a new mode to implement a neural network controller by installing a real object for control and an algorithm for this, which can replace the existing method of implementing a neural network controller by utilizing activation function at the output node. The real plant object for controlling of this mode implements a simple neural network controller replacing the activation function and provides the error back propagation path to calculate the error at the output node. As the controller is designed using a simple structure neural network, the input-output pattern problem is solved naturally and real-time learning becomes possible through the general error back propagation algorithm. The new algorithm applied neural network controller gives excellent performance for initial and tracking response and shows a robust performance for rapid load change and disturbance, in which the permissible error surpasses the range border. The effect of the proposed control algorithm was verified in a test that controlled the speed of a motor equipped with a high speed computing capable DSP on which the proposed algorithm was loaded.

• Proceedings of the KIEE Conference
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• 2005.10a
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• pp.155-157
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• 2005

This paper shows how to design a MPPT control of PV system using neural network PI self tuning. The conventional self-tuning methods have the voltage control problem of nonlinear PV system which can't adapt against any kinds of noise or operation circumstances. In this paper, supposed to solve these problem to PI parameters controller algorithm using ANN. In the proposed algorithm, the parameters of the controller were adjusted to reduce by on-line system the error of the output voltage of DC-DC chopper. In this process, EBPA NN was constituted to an output error value of a DC-DC chopper and conspired an input and output. The performance of the self-tuning controller is compared with that of the PI controller tuned by conventional method. The effectiveness of the proposed control method is verified thought the Matlab Simulink.

• Aerospace Engineering and Technology
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• v.13 no.1
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• pp.27-36
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• 2014

Generally, satellites continuously monitor that its major functions are working properly and their hardware are in a good status using several SOH data. In case a fault that is not recognized as a temporal problem or a failure that can be considered to propagate its damage to the other parts are detected, fault management logic is performed automatically without any contact of ground station. In this paper, attitude error detection using sun sensors on a rotating solar array is proposed. Attitude error can be detected by comparing the offset angle between the actual data computed from the sun sensor and the data predicted from the orbit and ephemeris information for the two types of solar array operation method. During the eclipse, the output of attitude error detection method becomes zero because the sun sensor output cannot be provided. Finally, the proposed method is analyzed through the data processing using on-orbit data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.11
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• pp.645-651
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• 2014

For blind equalization, we propose a method of updating an equalizer, which generates an error from selectively applying a transmitted symbol constellation and that of induced equivalently from the transmitted symbol constellation and updates the equalizer by using this error. The proposed method, by selectively using the symbol constellation effective for improvement of symbol estimation accuracy and that of effective for improvement of error performance, showed that it is possible to improve the error performance at the same time to open the eye diagram of equalizer output quickly. As a criterion applying the symbol constellation, we used the dispersion of symbol points of equalizer output. In addition, to increase the accuracy of updating an equalizer the error was controlled by using current and previous dispersions. By simulation, under multipath channel with additive noise, we verified the equalization performance of the proposed method for 64-QAM.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.101-105
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• 1989

The iterative learning controller makes the system output follow the desired output over a finite time interval through iterating trials. In this paper, first we discuss that the design problem of learning controller is originally the design problem of the inverse model. Then we show that the tracking error which is the difference between the desired output and the system output is reduced monotonically by properly modeled inverse system if the magnitude of the learning operator being introduced is bounded within the unit circle in complex domain. Also it would be shown that the conventional learning control method is a kind of extremely simplified inverse model learning control method of the objective controlled system. Hence this control method can be considered as a generalization of the conventional learning control method. The more a designer model the objective controlled system precisely, the better the performance of the approximated inverse model learning controller would be. Finally we compare the performance of the conventional learning control method with that of the approximated inverse model learning control method by computer simulation.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1593-1600
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• 2015

This paper proposes a novel compensation algorithm of current offset error for single-phase linear compressor in home appliances. In a half-bridge inverter, current offset error may cause unbalanced DC-link voltage when the DC-link is comprised of two serially connected capacitors. To compensate the current measurement error, the synchronous reference frame transformation is used for detecting the measurement error. When an offset error occurs in the output current of the half-bridge inverter, the d-axis current has a ripple with frequency equal to the fundamental frequency. With the use of a proportional-resonant controller, the ripple component can be removed, and offset error can be compensated. The proposed compensation method can easily be implemented without much computation and additional hardware circuit. The validity of the proposed algorithm is verified through experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.530-533
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• 1993

This paper describes a new method of dynamic error compensation, using a digital convolution integrator and two digital low pass filters. In this method, the process of compensation consists of three steps. First, sampling and digitizing of input signal, second, removing the noise in sampled data by the low pass filter and third, making a convolution integral using the output data of low pass filters. This method showed a good experimental result of reducing dynamic error even if there was a slight noise in the input signal. As a result, the detecting time constant of resistance thermo-bulb was improved to about 1/10th.