• Title/Summary/Keyword: nonlinear difference systems

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Development of Fuzzy controller for battery cell balancing of agricultural drones (농업용 드론의 배터리 셀 밸런싱을 위한 퍼지제어기 개발)

  • Lee, Sang-Hyun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.5
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    • pp.199-208
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    • 2017
  • Lithium polymer batteries are used in energy storage systems (ESS), electric vehicles (EVs), etc. due to their high safety, fast charging and long lifecycle, and now they are used in agricultural drones. However, when overcharging and overdischarging, the lithium-polymer battery is destroyed in the gap structure in the lithium-ion battery and the battery life is reduced. In order to prevent overcharge and overdischarge, uneven cell voltage Cell balancing system is needed. In this paper, a fuzzy controller suitable for nonlinear systems is proposed by detecting the unbalanced cells by detecting the voltage difference between charging and discharging of each cell, and suggesting the applied cell balancing algorithm. In this paper, we have designed the cell balancing of the battery pack of agricultural drones by fuzzy control and it is designed for equal control between cells. As a final result, we checked whether cell balancing is good, and when there are two cells, Cell balancing was confirmed. We tested whether it could be used for other products. As a result, we confirmed that cell balancing is good regardless of the number of cells used.

Finite Element Analysis of the Reinforced Concrete Boundary-Beam-Wall System Subjected to Axial Load (축하중이 작용하는 RC 경계보-벽체 시스템의 해석적 평가)

  • Son, Hong-Jun;Kim, Seung-Il;Kim, Dae-Jin
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.2
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    • pp.93-100
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    • 2021
  • In Korea, one of the most used structural systems for residential apartment buildings is the combination of the reinforced concrete (RC) wall and rahmen structures in the upper and lower floors, respectively. To alleviate the significant difference between the stiffnesses of these two structural systems, large transfer girders are generally required in the transition zone of the structure, which then results in the use of large amounts of construction materials and low economic feasibility. This paper proposes a new RC boundary-beam-wall system that can minimize the disadvantages of the RC transfer girder system. The structural performance of the proposed system subjected to axial loading was evaluated via rigorous three-dimensional nonlinear finite element analysis. Four parameters, namely the ratio of lower wall to upper wall lengths, distance between stirrups, main bar slope ratio, and slab length, were considered in the finite element analysis, and their effects on the maximum axial load were analyzed and discussed.

Numerical Analysis for Consolidation of Compressible Soils (압축성 모의 압밀에 대한 수치해석 -다층토를 중심으로-)

  • Kim, Pal-Gyu;Song, Yong-Hui;Lee, Hwan-Gi
    • Geotechnical Engineering
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    • v.1 no.1
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    • pp.5-12
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    • 1985
  • Ocassionally it is used for simple extensions of Terzahgi's theory to account for time-depend- tint loading but there is little evidence of application in more complicated consolidation theories that take into account such effects as nonlinear stress.strain, layered systems or large strains. The purpose of this paper provides an efficient computer algorthm based on numerical analysis using finite difference method which account for multi-layered soils to determine the degree of consolidation and excess pore pressures relative to time and positions more realistically. The explicitly scheme of solving the consolidation equations has been investigated from the point of view of the stability conditions and the convergence with variance of the operator as well as to obtain an optimal divided depth ratios of total depth. A comparison of the settlement predictions with both the classical analysis and the algorithm based on numerical analysis indicates that the new algorithm scheme is found to be superior to the classical theory in the layered soils.

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Evaluation of Pumping Rates for Multiple-Well Systems (군정 시스템의 취수량 평가)

  • Park, Nam-Sik;Kim, Sung-Yun;Kim, Boo-Gil;Kim, Il-Ryong
    • The Journal of Engineering Geology
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    • v.18 no.4
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    • pp.439-446
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    • 2008
  • We have developed a method to evaluate pumping rates from a system of pumping-well family. For a given system actual pumping rates depend on pump characteristics and the sum of the static head and the dynamic head. The static head is the elevation difference between the natural groundwater level and the outlet of the pipeline that connects all the wells. Major components of the dynamic head are groundwater drawdown in the well and pipeline head loss. The dynamic head and the pump characteristics depend on the pumping rates. Actual pumping rates are determined at the intersections of the system total-head curves and the pump characteristic curves. The Newton-Raphson's method is used to solve the nonlinear simultaneous equations. The method is applied to a hypothetical well family. Impacts of various design and operational parameters on the pumping rates are analyzed.

Numerical finite element study of a new perforated steel plate shear wall under cyclic loading

  • Farrokhi, Ali-Akbar;Rahimi, Sepideh;Beygi, Morteza Hosseinali;Hoseinzadeh, Mohamad
    • Earthquakes and Structures
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    • v.22 no.6
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    • pp.539-548
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    • 2022
  • Steel plate shear walls (SPSWs) are one of the most important and widely used lateral load-bearing systems. The reason for this is easier execution than reinforced concrete (RC) shear walls, faster construction time, and lower final weight of the structure. However, the main drawback of SPSWs is premature buckling in low drift ratios, which affects the energy absorption capacity and global performance of the system. To address this problem, two groups of SPSWs under cyclic loading were investigated using the finite element method (FEM). In the first group, several series of circular rings have been used and in the second group, a new type of SPSW with concentric circular rings (CCRs) has been introduced. Numerous parameters include in yield stress of steel plate wall materials, steel panel thickness, and ring width were considered in nonlinear static analysis. At first, a three-dimensional (3D) numerical model was validated using three sets of laboratory SPSWs and the difference in results between numerical models and experimental specimens was less than 5% in all cases. The results of numerical models revealed that the full SPSW undergoes shear buckling at a drift ratio of 0.2% and its hysteresis behavior has a pinching in the middle part of load-drift ratio curve. Whereas, in the two categories of proposed SPSWs, the hysteresis behavior is complete and stable, and in most cases no capacity degradation of up to 6% drift ratio has been observed. Also, in most numerical models, the tangential stiffness remains almost constant in each cycle. Finally, for the innovative SPSW, a relationship was suggested to determine the shear capacity of the proposed steel wall relative to the wall slenderness coefficient.

Research on data augmentation algorithm for time series based on deep learning

  • Shiyu Liu;Hongyan Qiao;Lianhong Yuan;Yuan Yuan;Jun Liu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.6
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    • pp.1530-1544
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    • 2023
  • Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

Numerical Simulation of Dynamic Soil-pile Interaction for Dry Condition Observed in Centrifuge Test (원심모형실험에서 관측된 건조 지반-말뚝 동적 상호작용의 수치 모델링)

  • Kown, Sun-Yong;Kim, Seok-Jung;Yoo, Min-Taek
    • Journal of the Korean Geotechnical Society
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    • v.32 no.4
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    • pp.5-14
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    • 2016
  • Numerical simulation of dynamic soil-pile-structure interaction embedded in a dry sand was carried out. 3D model of the dynamic centrifuge model tests was formulated in a time domain to consider nonlinear behavior of soil using the finite difference method program, FLAC3D. As a modeling methodology, Mohr-Coulomb criteria was adopted as soil constitutive model. Soil nonlinearity was considered by adopting the hysteretic damping model, and an interface model which can simulate separation and slip between soil and pile was adopted. Simplified continuum modeling (Kim et al., 2012) was used as boundary condition to reduce analysis time. Calibration process for numerical modeling results and test results was performed through the parametric study. Verification process was then performed by comparing numerical modeling results with another test results. Based on the calibration and validation procedure, it is identified that proposed modeling method can properly simulate dynamic behavior of soil-pile system in dry condition.

Implementation of Multiple Nonlinearities Control for Stable Walking of a Humanoid Robot (휴머노이드 로봇의 안정적 보행을 위한 다중 비선형 제어기 구현)

  • Kong, Jung-Shik;Kim, Jin-Geol;Lee, Bo-Hee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.2
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    • pp.215-221
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    • 2006
  • This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems such as the structural instability, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control were fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system by employing only single algorithm since the system usually includes multiple nonlinearities. In this paper, a switching Pill is considered for a control of saturation and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between the results of simulation and experiment, and then the switching Pill gains are determined using genetic algorithm with some heuristic approach. The performance of the switching Pill controller for saturation and the dual feedback for backlash control is investigated through the simulation. Finally, it is shown that the implemented control system has good results and can be applied to the real humanoid robot system ISHURO.

Effect of Lugol's Iodine Preservation on Cyanobacterial Biovolume and Estimate of Live Cell Biovolume Using Shrinkage Ratio (Lugol's Iodine Solution 첨가 후 보존 기간별 남조류 세포부피 변화 및 수축비를 이용한 생세포 부피 산정)

  • Park, Hae-Kyung;Lee, Hyeon-Je;Lee, Hae-Jin;Shin, Ra-Young
    • Journal of Korean Society on Water Environment
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    • v.34 no.4
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    • pp.375-381
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    • 2018
  • The monitoring of phytoplankton biomass and community structure is essential as a first step to control the harmful cyanobacterial blooms in freshwater systems, such as seen in rivers and lakes, due to the process of eutrophication and climate change. In order to quantify the biomass of phytoplankton with a wide range in size and shape, the measurement of cell biovolume along with cell density is required for a comprehensive review on this issue. However, most routine monitoring programs preserve the gathered phytoplankton samples before analysis using chemical additives, because of the constraint of time and the number of samples. The purpose of this study was to investigate the cell biovolume change characteristics of six cyanobacterial species, which are common bloom-causing cyanobacteria in the Nakdong River, after the preservation with Lugol's iodine solution. All species showed a statistically significant difference after the addition of Lugol's iodine solution compared to the live cell biovolume, and the cell biovolume decreased to the level of 34.0 ~ 56.3 % at maximum in each species after the preservation. The nonlinear regression models for determining the shrinkage ratio by a preservation period were derived by using the cell biovolume measured until 180 days preservation of each target species, and the equation to convert the cell biovolume measured after preservation for a certain period to the cell biovolume of viable cell was derived using that formula. The conversion equation derived from this study can be used to estimate the actual cell biovolume in the natural environment at the time of sampling, by using the measured biovolume after the preservation in the phytoplankton monitoring. Moreover this is expected to contribute to the final interpretation of the water quality and aquatic ecosystem impacts due to the cyanobacterial blooms.

The Prediction of DEA based Efficiency Rating for Venture Business Using Multi-class SVM (다분류 SVM을 이용한 DEA기반 벤처기업 효율성등급 예측모형)

  • Park, Ji-Young;Hong, Tae-Ho
    • Asia pacific journal of information systems
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    • v.19 no.2
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    • pp.139-155
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    • 2009
  • For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.