• Title/Summary/Keyword: Power feedforward

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An Adaptive Decision Feedback Equalizer for Underwater Acoustic Communications (수중음향통신을 위한 적응 결정궤환 등화기)

  • Choi, Young-Chol;Park, Jong-Won;Lim, Yong-Kon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.4
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    • pp.645-651
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    • 2009
  • In this paper, we present bit error rate(BER) performance of an adaptive decision feedback equalizer(DFE) using experimental data. The experiment was performed at the shore of Geoje in November 2007. The BER of the adaptive DFE whose tap weight is updated by RLS is described with change of feedforward filter length, feedback filter length, training sequence length, and delay, which shows that the uncoded average BER is $4{\times}10^2\;and\;1.5{\times}10^{-2}$ with transmission range of 9.7km and 4km, respectively. The BER of the adaptive DFE can be lower than 10-3 by a forward error correction code and therefore the adaptive DFE may be a good candidate for a high speed AUV communications since the volume and weight of the underwater acoustic modem should be small because of the restricted space and power in the battery-operated AUV.

Performance Comparisons of Wavelet Based T2-Test and Neural Network in Monitoring Process Profiles (공정프로파일 모니터링에서 웨이블릿기 반 T2-검정과 신경회로망의 성능비교)

  • Kim, Seong-Jun;Choi, Deok-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.6
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    • pp.737-745
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    • 2008
  • Recent developments of process and measurement technology bring much interest to the online monitoring of process operations such as milling, grinding, broaching, etc. The objective of online monitoring systems is to detect process changes as early as possible. This is helpful in protecting facilities against unexpected failures and then preventing unnecessary loss. This paper investigates, when the process monitoring data are obtained as a profile, the monitoring performances of a statistical $T^2$-statistic and a feedforward neural network by using a wavelet transform. Numerical experiments using cutting force data presented by Axinte show that the proposed wavelet based $T^2$-test has an acceptable power in detecting profile changes. However, its operating characteristic is very sensitive to autocorrelation. On the contrary, compared with $T^2$-test, the neural network has more stable performance in the presence of autocorrelation. This indicates that an adaptive feature to analyze noises should be incorporated into the wavelet based $T^2$-test.

Nonlinear Model-Based Robust Control of a Nuclear Reactor Using Adaptive PIF Gains and Variable Structure Controller (적응 PIF Gain 및 가변구조 제어기를 사용한 비선형 모델에 의한 원자로의 Robust Control)

  • Park, Moon-Ghu;Cho, Nam-Zin
    • Nuclear Engineering and Technology
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    • v.25 no.1
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    • pp.110-124
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    • 1993
  • A Nonlinear model-based Hybrid Controller (NHC) is developed which consists of the adaptive proportional-integral-feedforward (PIF) gains and variable structure controller. The controller has the robustness against modeling uncertainty and is applied to the trajectory tracking control of single-input, single-output nonlinear systems. The essence of the scheme is to divide the control into four different terms. Namely, the adaptive P-I-F gains and variable structure controller are used to accomplish the specific control actions by each terms. The robustness of the controller is guaranteed by the feedback of estimated uncertainty and the performance specification given by the adaptation of PIF gains using the second method of Lyapunov. The variable structure controller is incorporated to regulate the initial peak of the tracking error during the parameter adaptation is not settled yet. The newly developed NHC method is applied to the power tracking control of a nuclear reactor and the simulation results show great improvement in tracking performance compared with the conventional model-based control methods.

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Spatial Estimation of soil roughness and moisture from Sentinel-1 backscatter over Yanco sites: Artificial Neural Network, and Fractal

  • Lee, Ju Hyoung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.125-125
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    • 2020
  • European Space Agency's Sentinel-1 has an improved spatial and temporal resolution, as compared to previous satellite data such as Envisat Advanced SAR (ASAR) or Advanced Scatterometer (ASCAT). Thus, the assumption used for low-resolution retrieval algorithms used by ENVISAT ASAR or ASCAT is not applicable to Sentinel-1, because a higher degree of land surface heterogeneity should be considered for retrieval. The assumption of homogeneity over land surface is not valid any more. In this study, considering that soil roughness is one of the key parameters sensitive to soil moisture retrievals, various approaches are discussed. First, soil roughness is spatially inverted from Sentinel-1 backscattering over Yanco sites in Australia. Based upon this, Artificial Neural Networks data (feedforward multiplayer perception, MLP, Levenberg-Marquadt algorithm) are compared with Fractal approach (brownian fractal, Hurst exponent of 0.5). When using ANNs, training data are achieved from theoretical forward scattering models, Integral Equation Model (IEM). and Sentinel-1 measurements. The network is trained by 20 neurons and one hidden layer, and one input layer. On the other hand, fractal surface roughness is generated by fitting 1D power spectrum model with roughness spectra. Fractal roughness profile is produced by a stochastic process describing probability between two points, and Hurst exponent, as well as rms heights (a standard deviation of surface height). Main interest of this study is to estimate a spatial variability of roughness without the need of local measurements. This non-local approach is significant, because we operationally have to be independent from local stations, due to its few spatial coverage at the global level. More fundamentally, SAR roughness is much different from local measurements, Remote sensing data are influenced by incidence angle, large scale topography, or a mixing regime of sensors, although probe deployed in the field indicate point data. Finally, demerit and merit of these approaches will be discussed.

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Design of a Inverter-Based 3rd Order ΔΣ Modulator Using 1.5bit Comparators (1.5비트 비교기를 이용한 인버터 기반 3차 델타-시그마 변조기)

  • Choi, Jeong Hoon;Seong, Jae Hyeon;Yoon, Kwang Sub
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.7
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    • pp.39-46
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    • 2016
  • This paper describes the third order feedforward delta-sigma modulator with inverter-based integrators and a 1.5bit comparator for the application of audio signal processing. The proposed 3rd-order delta-sigma modulator is multi-bit structure using 1.5 bit comparator instead of operational amplifier. This delta-sigma modulator has high SNR compared with single-bit 4th-order delta-sigma modulator in a low OSR. And it minimizes power consumes and simplified circuit structure using inverter-based integrator and using inverter-based integrator as analogue adder. The modulator was designed with 0.18um CMOS standard process and total chip area is $0.36mm^2$. The measured power cosumption is 28.8uW in a 0.8V analog supply and 66.6uW in a 1.8V digital supply. The measurement result shows that the peak SNDR of 80.7 dB, the ENOB of 13.1bit and the dynamic range of 86.1 dB with an input signal frequency of 2.5kHz, a sampling frequency of 2.56MHz and an oversampling rate of 64. The FOM (Walden) from the measurement result is 269 fJ/step, FOM (Schreier) was calculated as 169.3 dB.

Recent Progress in Air-Conditioning and Refrigeration Research : A Review of Papers Published in the Korean Journal of Air-Conditioning and Refrigeration Engineering in 2010 (설비공학 분야의 최근 연구 동향 : 2010년 학회지 논문에 대한 종합적 고찰)

  • Han, Hwa-Taik;Lee, Dae-Young;Kim, Seo-Young;Choi, Jong-Min;Kim, Su-Min;Kwon, Young-Chul;Baik, Yong-Kyu
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.23 no.6
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    • pp.449-469
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    • 2011
  • This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering during 2010. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) Research trends of thermal and fluid engineering have been surveyed as groups of general thermal and fluid flow, fluid machinery, and new and renewable energy. Various topics were presented in the field of general thermal and fluid flow. Research issues mainly focused on the thermal reliability of axial fan and compressor in the field of fluid machinery. Studies on the design of ground source heat pump systems and solar chemical reactors were executed in the field of new and renewable energy. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics and industrial heat exchangers. Researches on heat transfer characteristics included heat transfer in thermoelectric cooling/power generation systems, combined heat and power systems, carbon nano fluid with PVP, channel filled with metal foam and smoke ventilation in a rescue station of a railroad tunnel. Also the studies on flow boiling of R123/oil mixture in a plain tube bundle and R410A charge amount in an air cooled mini-channel condenser were reported. In the area of industrial heat exchangers, researches on plate heat exchanger, shell and tube heat exchanger, enthalpy exchanger, micro channel PCHE were performed. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics and industrial heat exchangers. Researches on heat transfer characteristics included heat transfer in thermoelectric cooling/power generation systems, combined heat and power systems, carbon nano fluid with PVP, channel filled with metal foam and smoke ventilation in a rescue station of a railroad tunnel. Also the studies on flow boiling of R123/oil mixture in a plain tube bundle and R410A charge amount in an air cooled mini-channel condenser were reported. In the area of industrial heat exchangers, researches on plate heat exchanger, shell and tube heat exchanger, enthalpy exchanger, micro channel PCHE were performed. (3) Refrigeration systems with alternative refrigerants such as hydrocarbons, mixed refrigerants, and CO2 were studied. Performance improvement of refrigeration systems are tried applying various ideas of refrigerant subcooling, dual evaporator with hot gas bypass control and feedforward control. The hybrid solar systems combining the solar collection devices with absorption chillers or compression heat pumps are simulated and studied experimentally as well to improve the understanding and the feasibility for actual applications. (4) Research trend in the field of mechanical building facilities has been found to be mainly focused on field applications rather than performance improvements. Various studies on heating and cooling systems, HVAC facilities, indoor air environments and energy resources were carried to improve the maintenance and management of building service equipments. In the field of heating and cooling systems, papers on a transformer cooling system, a combined heat and power, a slab thermal storage and a heat pump were reported. In the field of HVAC facilities, papers on a cooling load, an ondol and a drying were presented. Also, studies on HVAC systems using unutilized indoor air environments and energy resources such as air curtains, bioviolence, cleanrooms, ventilation, district heating, landfill gas were studied. (5) In the field of architectural environment and energy, studies of various purposes were conducted such as indoor environment, building energy, renewable energy and green building. In particular, renewable energy and building energy-related researches have mainly been studied reflecting the global interest. In addition, many researches which related the domestic green building certification of school building were performed to improve the indoor environment of school.

High Gain Observer-based Robust Tracking Control of LIM for High Performance Automatic Picking System (고성능 자동피킹 시스템을 위한 선형 유도 모터의 고이득 관측기 기반의 강인 추종 제어)

  • Choi, Jung-Hyun;Kim, Jung-Su;Kim, Sanghoon;Yoo, Dong Sang;Kim, Kyeong-Hwa
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.1
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    • pp.7-14
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    • 2015
  • To implement an automatic picking system (APS) in distribution center with high precision and high dynamics, this paper presents a high gain observer-based robust speed controller design for a linear induction motor (LIM) drive. The force disturbance as well as the mechanical parameter variations such as the mass and friction coefficient gives a direct influence on the speed control performance of APS. To guarantee a robust control performance, the system uncertainty caused by the force disturbance and mechanical parameter variations is estimated through a high gain disturbance observer and compensated by a feedforward manner. While a time-varying disturbance due to the mass variation can not be effectively compensated by using the conventional disturbance observer, the proposed scheme shows a robust performance in the presence of such uncertainty. A Simulink library has been developed for the LIM model from the state equation. Through comparative simulations based on Matlab - Simulink, it is proved that the proposed scheme has a robust control nature and is most suitable for APS.

A Study on GA-based Optimized Polynomial Neural Networks and Its Application to Nonlinear Process (유전자 알고리즘 기반 최적 다항식 뉴럴네트워크 연구 및 비선형 공정으로의 응용)

  • Kim Wan-Su;Lee In-Tae;Oh Sung-Kwun;Kim Hyun-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.7
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    • pp.846-851
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    • 2005
  • In this paper, we propose Genetic Algorithms(GAs)-based Optimized Polynomial Neural Networks(PNN). The proposed algorithm is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional neural networks and can be generated in a dynamic manner. As each node of PNN structure, we use several types of high-order polynomial such as linear, quadratic and modified quadratic, and it is connected as various kinds of multi-variable inputs. The conventional PNN depends on the experience of a designer that select the number of input variables, input variable and polynomial type. Therefore it is very difficult to organize optimized network. The proposed algorithm leads to identify and select the number of input variables, input variable and polynomial type by using Genetic Algorithms(GAs). The aggregate performance index with weighting factor is proposed as well. The study is illustrated with tile NOx omission process data of gas turbine power plant for application to nonlinear process. In the sequel the proposed model shows not only superb predictability but also high accuracy in comparison to the existing intelligent models.