• 제목/요약/키워드: Model-based systems engineering

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Indirect Adaptive Fuzzy Observer Design

  • Yang, Jong-Kun;Hyun, Chang-Ho;Kim, Jae-Hun;Kim, Eun-Tai;Park, Mi-Gnon
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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    • pp.192-196
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    • 2004
  • This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

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Indirect Adaptive Fuzzy Observer Design

  • Yang, Jong-Kun;Hyun, Chang-Ho;Kim, Jae-Hun;Kim, Eun-Tai;Park, Mignon
    • 한국지능시스템학회논문지
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    • 제14권7호
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    • pp.927-933
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    • 2004
  • This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

Optimization of Fuzzy Set-Fuzzy Systems based on IG by Means of GAs with Successive Tuning Method

  • Park, Keon-Jun;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Journal of Electrical Engineering and Technology
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    • 제3권1호
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    • pp.101-107
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    • 2008
  • We introduce an optimization of fuzzy set-fuzzy systems based on IG (Information Granules). The proposed fuzzy model implements system structure and parameter identification by means of IG and GAs. The concept of information granulation was coped with to enhance the abilities of structural optimization of the fuzzy model. Granulation of information realized with C-Means clustering helps determine the initial parameters of the fuzzy model such as the initial apexes of the membership functions in the premise part and the initial values of polynomial functions in the consequence part of the fuzzy rules. The initial parameters are adjusted effectively with the help of the GAs and the standard least square method. To optimally identify the structure and the parameters of the fuzzy model we exploit GAs with successive tuning method to simultaneously search the structure and the parameters within one individual. We also consider the variant generation-based evolution to adjust the rate of identification of the structure and the parameters in successive tuning method. The proposed model is evaluated with the performance of the conventional fuzzy model.

Machine learning-based analysis and prediction model on the strengthening mechanism of biopolymer-based soil treatment

  • Haejin Lee;Jaemin Lee;Seunghwa Ryu;Ilhan Chang
    • Geomechanics and Engineering
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    • 제36권4호
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    • pp.381-390
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    • 2024
  • The introduction of bio-based materials has been recommended in the geotechnical engineering field to reduce environmental pollutants such as heavy metals and greenhouse gases. However, bio-treated soil methods face limitations in field application due to short research periods and insufficient verification of engineering performance, especially when compared to conventional materials like cement. Therefore, this study aimed to develop a machine learning model for predicting the unconfined compressive strength, a representative soil property, of biopolymer-based soil treatment (BPST). Four machine learning algorithms were compared to determine a suitable model, including linear regression (LR), support vector regression (SVR), random forest (RF), and neural network (NN). Except for LR, the SVR, RF, and NN algorithms exhibited high predictive performance with an R2 value of 0.98 or higher. The permutation feature importance technique was used to identify the main factors affecting the strength enhancement of BPST. The results indicated that the unconfined compressive strength of BPST is affected by mean particle size, followed by biopolymer content and water content. With a reliable prediction model, the proposed model can present guidelines prior to laboratory testing and field application, thereby saving a significant amount of time and money.

Product Configuration Model 개념 기반의 함정 건조공수 추정 연구 (Construction Cost Estimation on the Initial Design Stage of Naval Ships based on a Product Configuration Model)

  • 오대균;정연환;신종계;최양열
    • 대한조선학회논문집
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    • 제46권3호
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    • pp.351-361
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    • 2009
  • Many manufacturers define the system of a new product flexibility, and take advantage of previous-product information using the product configuration concept. Product configuration is an approach that defines the system of a new product centered on the product structure by referring to the previous-product information. In this paper, it is established how to apply the concept of a product configuration utilizing previous-ships information in construction cost estimation process systematically and effectively. For this, we define the advanced-construction cost estimation process based on a naval ship product model, and design construction cost estimating model. It is validated that this process and model have the applicability through the case study of the construction cost estimating of the mine-warfare ship.

SysML 을 이용한 선체 곡판가공 자동화 시스템 모델링 (A Modeling of Automated Hull Curved Plates Forming System using SysML)

  • 노재규;신종계
    • 시스템엔지니어링학술지
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    • 제4권2호
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    • pp.1-13
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    • 2008
  • The development of hull curved plate forming automation system in ship production field begins from the need of stakeholders such as enterprise organization, who need the reduction of cost and time and improvement of productivity, and end users who work for this production process. Even though hull curved plate forming automation system has small scale, it is reasonable to consider the system as an interdisciplinary system, because the system includes all of hardware, software, human and information and has a specified objective to be performed. In this paper, introduction of 4 leading Model-Based Systems Engineering (MBSE)methodologies is described and SysML(Systems Modeling Language), which is designed to analyze, specify, design, and verify complex systems, is introduced in order to support those methodologies. Especially, SysML is applied to system modeling of hull curved plate forming automation system and focused on. The structure diagrams and behavior diagrams based on operational context of the automation system are used to make system architecture. The performed application of SysML to the hull curved plate forming automation system shows an example of applying SysML to the development of other autonomous systems in ship production domain.

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Sampled-Data Observer-Based Decentralized Fuzzy Control for Nonlinear Large-Scale Systems

  • Koo, Geun Bum;Park, Jin Bae;Joo, Young Hoon
    • Journal of Electrical Engineering and Technology
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    • 제11권3호
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    • pp.724-732
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    • 2016
  • In this paper, a sampled-data observer-based decentralized fuzzy control technique is proposed for a class of nonlinear large-scale systems, which can be represented to a Takagi-Sugeno fuzzy system. The premise variable is assumed to be measurable for the design of the observer-based fuzzy controller, and the closed-loop system is obtained. Based on an exact discretized model of the closed-loop system, the stability condition is derived for the closed-loop system. Also, the stability condition is converted into the linear matrix inequality (LMI) format. Finally, an example is provided to verify the effectiveness of the proposed techniques.

A Neoteric Three-Dimensional Geometry-Based Stochastic Model for Massive MIMO Fading Channels in Subway Tunnels

  • Jiang, Yukang;Guo, Aihuang;Zou, Jinbai;Ai, Bo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권6호
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    • pp.2893-2907
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    • 2019
  • Wireless mobile communication systems in subway tunnels have been widely researched these years, due to increased demand for the communication applications. As a result, an accurate model is essential to effectively evaluate the communication system performance. Thus, a neoteric three-dimensional (3D) geometry-based stochastic model (GBSM) is proposed for the massive multiple-input multiple-output (MIMO) fading channels in tunnel environment. Furthermore, the statistical properties of the channel such as space-time correlation, amplitude and phase probability density are analyzed and compared with those of the traditional two-dimensional (2D) model by numerical simulations. Finally, the ergodic capacity is investigated based on the proposed model. Numerical results show that the proposed model can describe the channel in tunnels more practically.

Evaluation of an Abstract Component Model for Embedded Systems Development

  • Bunse, Christian;Choi, Yunja;Gross, Hans Gerhard
    • Journal of Information Processing Systems
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    • 제8권4호
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    • pp.539-554
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    • 2012
  • Model-driven and component-oriented development is increasingly being used in the development of embedded systems. When combined, both paradigms provide several advantages, such as higher reuse rates, and improved system quality. Performing model-driven and component-oriented development should be accompanied by a component model and a method that prescribes how the component model is used. This article provides an overview on the MARMOT method, which consists of an abstract component model and a methodology for the development of embedded systems. The paper describes a feasibility study that demonstrates MARMOT's capability to alleviate system design, verification, implementation, and reuse. Results indicate that model-driven and component-based development following the MARMOT method outperforms Agile development for embedded systems, leads to maintainable systems, and higher than normal reuse rates.

Intelligent Digital Redesign Based on Periodic Control

  • Kim Do Wan;Joo Young Hoon;Park Jin Bae
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
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    • pp.378-381
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    • 2005
  • This paper presents a new linear-matrix-inequality-based intelligent digital redesign (LMI-based IDR) technique to match the states of the analog and the digital T-S fuzzy control systems at the intersampling instants as well as the sampling ones. The main features of the proposed technique are: 1) the fuzzy-model-based periodic control is employed, and the control input is changed n times during one sampling period; 2) The proposed IDR technique is based on the approximately discretized version of the T-S fuzzy system, but its discretization error vanishes as n approaches the infinity. 3) some sufficient conditions involved in the state matching and the stability of the closed-loop discrete-time system can be formulated in the LMIs format.

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