• Biotechnology and Bioprocess Engineering:BBE
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• v.7 no.2
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• pp.76-84
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• 2002

On-line conversion estimation of enzymatic esterification reactions in solvent-free media was investigated. In principle, conversion to ester can be determined from the amount of water produced by the reaction, because water is formed as a by-product in a stoichiometric manner. In this study, we estimated the water production rate only from some measurements of relative humidity and water balances without using any analytical methods. In order to test the performance of the on-line conversion estimation, the lipase-catalyzed esterification of n-capric acid and n-decal alcohol in solvent-free media was performed whilst controlling water activity at various values. The reaction conversions estimated on-line were similar to those determined by offline gas chromatographic analysis. However, when the water activity was controlled at higher values, discrepancies between the estimated conversion values and the measured values became significant. The deviation was found to be due to the inaccurate measurement of the water content in the reaction medium during the initial stages of the reaction. Using a digital filter, we were able to improve the accuracy of the on-line conversion estimation method considerably. Despite the simplicity of this method, the on-line estimated conversions were in good agreement with the off-line measured values.

• Journal of Power Electronics
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• v.13 no.4
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• pp.516-527
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• 2013

This paper presents a new overall system for state-of-available-power (SoAP) prediction for a lithium-ion battery pack. The essential part of this method is based on an adaptive network architecture which utilizes both fuzzy model (FIS) and artificial neural network (ANN) into the framework of adaptive neuro-fuzzy inference system (ANFIS). While battery aging proceeds, the system is capable of delivering accurate power prediction not only for room temperature, but also at lower temperatures at which power prediction is most challenging. Due to design property of ANN, the network parameters are adapted on-line to the current battery states (state-of-charge (SoC), state-of-health (SoH), temperature). SoC is required as an input parameter to SoAP module and high accuracy is crucial for a reliable on-line adaptation. Therefore, a reasonable way to determine the battery state variables is proposed applying a combination of several partly different algorithms. Among other SoC boundary estimation methods, robust extended Kalman filter (REKF) for recalibration of amp hour counters was implemented. ANFIS then achieves the SoAP estimation by means of time forward voltage prognosis (TFVP) before a power pulse occurs. The trade-off between computational cost of batch-learning and accuracy during on-line adaptation was optimized resulting in a real-time system with TFVP absolute error less than 1%. The verification was performed on a software-in-the-loop test bench setup using a 53 Ah lithium-ion cell.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.97-102
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• 2003

In this paper, a recurrent artificial neural network (RNN) based self-tuning speed controller is proposed for the high-performance drives of induction motors. The RNN provides a nonlinear modeling of a motor drive system and could provide the controller with information regarding the load variation system noise, and parameter variation of the induction motor through the on-line estimated weights of the corresponding RNN. Thus, the proposed self-tuning controller can change the gains of the controller according to system conditions. The gain is composed with the weights of the RNN. For the on-line estimation of the RNN weights, an extended Kalman filter (EKF) algorithm is used. A self-tuning controller is designed that is adequate for the speed control of the induction motor The availability of the proposed controller is verified through MATLAB simulations and is compared with the conventional PI controller.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.4
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• pp.206-210
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• 2004

This paper deals with a parameter estimation of the DC-DC converter system for its diagnosis. Especially, we present the results of parameter estimation for the DC-DC converter model by the system identification method. The parameter estimation for the DC-DC converter system aims at the diagnosis of its operating status. For the operating status diagnosis of the DC-DC converter system, we assume that the DC-DC converter system is an equivalent model of the Buck converter and estimate the main parameter for on-line diagnosis. In addition, for verification of an estimated parameter, we compare a bode plot of the estimated system transfer function and measurement results of the HP4194 instrument. It is a control system analyzer for system transfer function measurement. Our results confirm that the main parameter for diagnosis of the DC-DC converter system can be estimated by the system identification method and that the aging status of the system can be predicted by these results on operating status.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.661-672
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• 2017

This paper introduces the NLSE(Nonlinear Least Squared Estimator) using curved LOBs(Line Of Bearings) considering the earth curvature based on sphere to avoid the map conversion distortion and minimize the estimation error. This paper suggests a method improving a performance of the NLSE using curved LOBs by using an ellipsoid model. The analysis of the simulation results shows that the NLSE using curved LOBs has better performance than the conventional triangulation method and can improve its performance using a suggested method.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.43.3-43.3
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• 2019

A coronal mass ejection (CME) mass is generally estimated by the total brightness measured from white-light coronagraph observations. The total brightness are determined from the integration of the Thomson scattering by free electrons of solar corona along the line of sight. It is difficult to estimate the masses of halo CMEs due to the projection effect. To solve this issue, we construct a synthetic halo CME with a power-law density distribution (ρ = ρ₀r^-3) based on a full ice-cream cone model using SOHO/LASCO C3 observations. Then we compute a conversion factor from observed CME mass to CME mass for each CME. The final CME mass is determined as their average value of several CME masses above 10 solar radii. Our preliminary analysis for six CMEs show that their CME mass are well determined within the mean absolute relative error in the range of 4 to 15 %.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.5
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• pp.445-457
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• 2017

In this study, we developed an approach to better account for uncertainties in estimated contributions from fine particulate matter ($PM_{2.5}$) modeling. Our approach computes a Concentration Correction Factor (CCF) which is a ratio of observed concentrations to baseline model concentrations. We multiply modeled direct contribution estimates with CCF to obtain revised contributions. Overall, the modeling system showed reasonably good performance, correlation coefficient R of 0.82 and normalized mean bias of 2%, although the model underestimated some PM species concentrations. We also noticed that model biases vary seasonally. We compared contribution estimates of major source sectors before and after applying CCFs. We observed that different source sectors showed variable magnitudes of sensitivities to the CCF application. For example, the total primary $PM_{2.5}$ contribution was increased $2.4{\mu}g/m^3$ or 63% after the CCF application. Out of a $2.4{\mu}g/m^3$ increment, line sources and area source made up $1.3{\mu}g/m^3$ and $0.9{\mu}g/m^3$ which is 92% of the total contribution changes. We postulated two major reasons for variations in estimated contributions after the CCF application: (1) monthly variability of unadjusted contributions due to emission source characteristics and (2) physico-chemical differences in environmental conditions that emitted precursors undergo. Since emissions-to-$PM_{2.5}$ concentration conversion rate is an important piece of information to prioritize control strategy, we examined the effects of CCF application on the estimated conversion rates. We found that the application of CCFs can alter the rank of conversion efficiencies of source sectors. Finally, we discussed caveats of our current approach such as no consideration of ion neutralization which warrants further studies.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.1
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• pp.10-19
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• 2018

In this paper, a new high-frequency equivalent circuit model of printed spiral coils (PSCs) for radio-frequency interference (RFI) measurement has been proposed. To achieve high-frequency modeling, the proposed model consists of distributed components designed based on the design parameters of the PSCs. In addition, an analytic model for PSCs based on T-pi conversion has been proposed. To investigate the feasibility of the proposed model for RFI measurement, the transfer function between a microstrip line and a PSC has been extracted by combining the proposed model and mutual inductance. The self-impedances of the proposed model and the transfer function have been successfully validated using three-dimensional field simulation and measurements, revealing noticeable correlations up to a frequency of 6 GHz. The proposed model can be employed for high-frequency probe design and RFI noise estimation in the gigahertz range wireless communication bands.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.8
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• pp.1172-1180
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• 2013

Two experiments were conducted to determine the standardized ileal digestible (SID) lysine (Lys) requirement and the ideal SID threonine (Thr) to Lys ratio for finishing barrows. In Exp. 1, 120 barrows with an average body weight of $72.8{\pm}3.6$ kg were allotted to one of six dietary treatments in a randomized complete block design conducted for 35 d. Each diet was fed to five pens of pigs containing four barrows. A normal crude protein (CP) diet providing 15.3% CP and 0.71% SID Lys and five low CP diets providing 12% CP with SID Lys concentrations of 0.51, 0.61, 0.71, 0.81 and 0.91% were formulated. Increasing the SID Lys content of the diet resulted in an increase in weight gain (linear effect p = 0.04 and quadratic effect p = 0.08) and an improvement in feed conversion ratio (FCR) (linear effect p = 0.02 and quadratic effect p = 0.02). For weight gain and FCR, the estimated SID Lys requirement of finishing barrows were 0.71 and 0.71% (linear broken-line analysis), 0.79 and 0.78% (quadratic analysis), respectively. Exp. 2 was a 26 d dose-response study using SID Thr to Lys ratios of 0.56, 0.61, 0.67, 0.72 and 0.77. A total of 138 barrows weighing $72.5{\pm}4.4$ kg were randomly allotted to receive one of the five diets. All diets were formulated to contain 0.61% SID Lys (10.5% CP), which is slightly lower than the pig's requirement. Weight gain was quadratically (p = 0.03) affected by SID Thr to Lys ratio while FCR was linearly improved (p = 0.02). The SID Thr to Lys ratios for maximal weight gain and minimal FCR and serum urea nitrogen (SUN) were 0.67, 0.71 and 0.64 using a linear broken-line model and 0.68, 0.78 and 0.70 using a quadratic model, respectively. Based on the estimates obtained from the broken-line and quadratic analysis, we concluded that the dietary SID Lys requirement for both maximum weight gain and minimum FCR was 0.75%, and an optimum SID Thr to Lys ratio was 0.68 to maximize weight gain, 0.75 to optimize FCR and 0.67 to minimize SUN for finishing barrows.