• Journal of Power Electronics
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• v.13 no.1
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• pp.139-160
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• 2013

In this paper, an intelligent robust control system (IRCS) for precision tracking control of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The IRCS comprises a recurrent wavelet-based interval type-2 fuzzy-neural-network controller (RWIT2FNNC), an RWIT2FNN estimator (RWIT2FNNE) and a compensated controller. The RWIT2FNNC combines the merits of a self-constructing interval type-2 fuzzy logic system, a recurrent neural network and a wavelet neural network. Moreover, it performs the structure and parameter-learning concurrently. The RWIT2FNNC is used as the main tracking controller to mimic the ideal control law (ICL) while the RWIT2FNNE is developed to approximate an unknown dynamic function including the lumped parameter uncertainty. Furthermore, the compensated controller is designed to achieve $L_2$ tracking performance with a desired attenuation level and to deal with uncertainties including approximation errors, optimal parameter vectors and higher order terms in the Taylor series. Moreover, the adaptive learning algorithms for the compensated controller and the RWIT2FNNE are derived by using the Lyapunov stability theorem to train the parameters of the RWIT2FNNE online. A computer simulation and an experimental system are developed to validate the effectiveness of the proposed IRCS. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the IRCS grants robust performance and precise response regardless of load disturbances and PMSM parameters uncertainties.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5C
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• pp.317-325
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• 2011

For OFDM (Orthogonal Frequency Division Multiplexing) systems, 2-D MMSE (2-Dimensional Minimum Mean Square Error) channel estimation provides optimal performance in frequency/time selective fading channel environment. However, the 2-D MMSE channel estimation has high computational complexity due to the large matrix size, because the 2-D MMSE channel estimation considers time as well as frequency axis for channel estimation. To reduce the computational complexity, we propose a modified 2-D MMSE channel estimator which is based on 1-D MMSE channel estimation with weighted sum. Furthermore, we consider RMS delay spread and Doppler frequency estimation for 2-D MMSE channel estimation. We show that the proposed method can significantly reduce computational complexity as well as that it can perform close to 2-D MMSE channel estimation.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.1
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• pp.81-90
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• 2002

This paper presents an Implementation of digital high-performance position sensorless control system of Reluctance Synchronous Motor(RSM) drives with Direct Torque Control(DTC). The system consists of stator flux observer, speed and torque estimator, two digital hysteresis controllers, an optimal switching look-up table, Insulated Gate Bipolar Transistor(IGBT) voltage source inverter, and TMS320C31 DSP board. The stator flux observer Is based on the combined voltage and current model with stator flux feedback adaptive control of which inputs are current and voltage sensed on motor terminal for wide speed range. In order to prove the suggested sensorless control algorithm for industrial field application, we have some simulation and actual experiment at low and high speed range. The developed high-performance speed control by fully digital system are shown a good response characteristic of control results and high performance features using 1.0[kW] RSM having 2.57 reluctance ratio of $L_d/L_q$.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.10-21
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• 2023

For various target tracking applications, it is well known that the Kalman filter is the optimal estimator(in the minimum mean-square sense) to predict and estimate the state(position and/or velocity) of linear dynamical systems driven by Gaussian stochastic noise. In the case of nonlinear systems, Extended Kalman filter(EKF) and/or Unscented Kalman filter(UKF) are widely used, which can be viewed as approximations of the(linear) Kalman filter in the sense of the conditional expectation. However, to implement EKF and UKF, the exact dynamical model information and the statistical information of noise are still required. In this paper, we propose the recurrent neural-network based Kalman filter, where its Kalman gain is obtained via the proposed GRU-LSTM based neural-network framework that does not need the precise model information as well as the noise covariance information. By the proposed neural-network based Kalman filter, the state estimation performance is enhanced in terms of the tracking error, which is verified through various linear and nonlinear tracking problems with incomplete model and statistical covariance information.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.533-541
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• 2007

The Zienkiewicz-Zhu(Z/Z) error estimate is slightly modified for the hierarchical p-refinement, and is then applied to L-shaped plates subjected to bending to demonstrate its effectiveness. An adaptive procedure in finite element analysis is presented by p-refinement of meshes in conjunction with a posteriori error estimator that is based on the superconvergent patch recovery(SPR) technique. The modified Z/Z error estimate p-refinement is different from the conventional approach because the high order shape functions based on integrals of Legendre polynomials are used to interpolate displacements within an element, on the other hand, the same order of basis function based on Pascal's triangle tree is also used to interpolate recovered stresses. The least-square method is used to fit a polynomial to the stresses computed at the sampling points. The strategy of finding a nearly optimal distribution of polynomial degrees on a fixed finite element mesh is discussed such that a particular element has to be refined automatically to obtain an acceptable level of accuracy by increasing p-levels non-uniformly or selectively. It is noted that the error decreases rapidly with an increase in the number of degrees of freedom and the sequences of p-distributions obtained by the proposed error indicator closely follow the optimal trajectory.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.591-598
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• 2021

The digital phase-locked loops(DPLL) is a circuit used for phase synchronization and has been generally used in various fields such as communication and circuit fields. State estimators are used to design digital phase-locked loops, and infinite impulse response state estimators such as the well-known Kalman filter have been used. In general, the performance of the infinite impulse response state estimator-based digital phase-locked loop is excellent, but a sudden performance degradation may occur in unexpected situations such as inaccuracy of initial value, model error, and disturbance. In this paper, we propose a minimum variance finite impulse response filter with optimal horizon for designing a new digital phase-locked loop. A numerical method is introduced to obtain the measured value interval length, which is an important parameter of the proposed finite impulse response filter, and to obtain a gain, the covariance matrix of the error is set as a cost function, and a linear matrix inequality is used to minimize it. In order to verify the superiority and robustness of the proposed digital phase-locked loop, a simulation was performed for comparison and analysis with the existing method in a situation where noise information was inaccurate.

• Journal of Animal Science and Technology
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• v.49 no.5
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• pp.677-688
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• 2007

돼지를 포함한 대부분의 동물은 일정한 발정주기를 가지고 일정한 시기에 배란을 하는 자연배란동물이지만, 토끼, 고양이, 밍크 등의 암놈은 교미자극에 의해 배란이 일어나는 유기배란동물이다. 또한 1년에 한 번만 발정하는 단발정동물과 1년에 수차례 발정하는 다발정동물이 있다. 이 중에서 모돈은 1년에 수차례 발정하는 다발정 동물로서 발정기에 들면 비발정기와는 다른 행동을 나타낸다(Diehl 등, 2001). 양돈가의 수익을 최대화하기 위해서는 비생산일수를 최소로 줄여야 한다. 모돈의 비생산일수를 줄일 수 있는 한 가지 방법은 성공적으로 교배를 시키는 것이다. 이처럼 성공적으로 교배를 시키기 위해서는 수정적기를 정확히 예측해야 한다. 만약 수정적기를 정확히 판단하지 못하여 수태가 되지 않으면, 비생산일수가 늘어나 손실을 입게 된다. 따라서 수정적기를 정확히 판단하는 것은 모돈의 성공적인 인공수정에 있어서 중요한 요소이다. 수정적기는 배란이 일어나기 전 10시간에서 12시간 사이이며, 발정이 시작되는 시점을 기준으로 하였을 때 경산돈의 경우 26시간에서 34시간 사이이고 미경산돈의 경우는 18시간에서 26시간 사이이다(Evans 등, 2001). 현재 하루에 두 번 모돈의 발정을 확인하는 것이 일반화되어 있으며, 이 때 웅돈을 접촉시키거나 육안관찰을 통하여 발정 유무를 판단한다. 이러한 방법에는 숙련된 기술과 풍부한 경험이 요구될 뿐만 아니라 총 소요노동력의 30% 정도가 요구된다(Perez 등, 1986). 하루에 두 번밖에 발정을 감지하지 않기 때문에 발정이 언제 시작되었는지를 정확히 알 수 없으며, 또한 발정의 대부분이 새벽에 시작되므로 수정적기를 정확히 판단하기란 매우 어렵다. 만약 발정을 감지했더라도 적기에 인공수정을 하지 못한다면, 수태율이 낮아지므로 경제적 손실이 초래된다. 현재 이러한 문제점 때문에 2회에서 3회에 걸쳐 인공수정을 하고 있으나 이에 따른 소요비용과 소요노동력 등은 양돈가의 부담을 가중시키는 요인이 되고 있다. 돼지는 발정기가 되면 비발정기에 나타내지 않던 외음부의 냄새를 맡는 행동, 귀를 세우는 행동 및 승가허용 행동 등을 나타낸다(Diehl 등, 2001). 또한 돼지는 비발정기에 비하여 발정기에 더 많은 활동량을 나타낸다(Altman, 1941; Erez and Hartsock, 1990). Freson 등(1998)은 스톨에서 개별적으로 사육되고 있는 모돈의 활동량을 적외선센서를 이용하여 측정함으로써 발정을 86%까지 감지하였다고 보고하였다. 그러나 이 연구는 단지 모돈의 발정을 감지하였을 뿐 번식관리에 있어서 가장 중요한 수정적기의 판단 기준을 제시하지 못하였다. 따라서, 본 연구는 스톨에서 사육되는 모돈의 활동량을 측정함으로써 발정시작시각을 감지하고 이를 기준으로 인공수정적기를 예측할 수 있는 인공수정적기 예측 장치를 개발한 후 이의 성능을 농장실증실험을 통하여 시험하고자 수행되었다.

• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.52-60
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• 1999

Objectives: With the object of finding the appropriate conditions and algorithms for dimensional analysis of human EEG, we calculated correlation dimensions in the various condition of sampling rate and data aquisition time and improved the computation algorithm by taking advantage of bit operation instead of log operation. Methods: EEG signals from 13 scalp lead of a man were digitized with A-D converter under the condition of 12 bit resolution and 1000 Hertz of sampling rate during 32 seconds. From the original data, we made 15 time series data which have different sampling rate of 62.5, 125, 250, 500, 1000 hertz and data acqusition time of 10, 20, 30 second, respectively. New algorithm to shorten the calculation time using bit operation and the Least Trimmed Squares(LTS) estimator to get the optimal slope was applied to these data. Results: The values of the correlation dimension showed the increasing pattern as the data acquisition time becomes longer. The data with sampling rate of 62.5 Hz showed the highest value of correlation dimension regardless of sampling time but the correlation dimension at other sampling rates revealed similar values. The computation with bit operation instead of log operation had a statistically significant effect of shortening of calculation time and LTS method estimated more stably the slope of correlation dimension than the Least Squares estimator. Conclusion: The bit operation and LTS methods were successfully utilized to time-saving and efficient calculation of correlation dimension. In addition, time series of 20-sec length with sampling rate of 125 Hz was adequate to estimate the dimensional complexity of human EEG.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.149-160
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• 2015

This study aims to estimate the forest volumes of the upper region of Nam-Han River in ecosystem zoning by forest types and age classes, and to suggest the optimal estimation method through the comparison of the standard errors according to the spatial unit. In the estimation of forest volumes, we used both of direct estimation, which uses sample plots of the target area only, and synthetic estimation, which includes sample plots of the expanded areas as well as those of the target area. As for the spatial expansion, we applied four standards for synthetic estimator: Mountainous zone, Neighbor ecosystem region, Gangwon province, and Buffer zone. The results show that average forest volume per ha, calculated by direct estimation, was $143.5m^3/ha$, while that by synthetic estimation with each standard, was estimated at $146.9m^3/ha$ by Gangwon province, $144.8m^3/ha$ by Buffer zone, $139.8m^3/ha$ by Neighbor ecosystem region, and $138.6m^3/ha$ by Mountainous zone, respectively. The standard errors of direct estimation was $1.79m^3/ha$, while those of synthetic estimation showed not a great difference among the errors. Meanwhile, considering the standard errors by forest type, the lowest was ${\pm}2.3m^3/ha$ of broad-leaved forest, followed by ${\pm}3.3m^3/ha$ of mixed forest, and ${\pm}4.8m^3/ha$ of coniferous forest.