• 제목/요약/키워드: fuzzy programming

검색결과 188건 처리시간 0.026초

Real-time EtherCAT Master Implementation on Xenomai for a Robot System

  • Moon, Yong-Seon;Ko, Nak-Yong;Lee, Kwang-Seok;Bae, Young-Chul;Park, Jong-Kyu
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제9권3호
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    • pp.244-248
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    • 2009
  • This paper describes a real-time EtherCAT Master library. The library is developed using Xenomai. Xenomai is a real-time development framework. It cooperates with the Linux kernel, in order to provide a pervasive, interface-agnostic, hard real-time support to user-space applications, seamlessly integrated into the GNU/Linux environment. The proposed master library implements EtherCAT protocol for master side, and supports Application Programming Interfaces(APIs) for programming of real-time application which controls EtherCAT slave.

Improvement of Support Vector Clustering using Evolutionary Programming and Bootstrap

  • Jun, Sung-Hae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권3호
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    • pp.196-201
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    • 2008
  • Statistical learning theory has three analytical tools which are support vector machine, support vector regression, and support vector clustering for classification, regression, and clustering respectively. In general, their performances are good because they are constructed by convex optimization. But, there are some problems in the methods. One of the problems is the subjective determination of the parameters for kernel function and regularization by the arts of researchers. Also, the results of the learning machines are depended on the selected parameters. In this paper, we propose an efficient method for objective determination of the parameters of support vector clustering which is the clustering method of statistical learning theory. Using evolutionary algorithm and bootstrap method, we select the parameters of kernel function and regularization constant objectively. To verify improved performances of proposed research, we compare our method with established learning algorithms using the data sets form ucr machine learning repository and synthetic data.

불평형배전계통에서 부하모형을 고려한 분산형전원의 설치 및 운영계획 (Placement and Operation Planning of DG System considering Load Modeling in Unbalanced Distribution Systems)

  • 김규호;이유정;이상봉;이상근;유석구
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 A
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    • pp.396-398
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    • 2003
  • This paper presents the scheme for load model based dispersed generation system (DGs) installation and operation in unbalanced distribution systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load. The main idea of solving fuzzy nonlinear goal programming is to transform the original objective function and constraints into the equivalent multiple objective functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithms. The method proposed was applied to IEEE 13 bus test systems to demonstrate its effectiveness.

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볼록 최적화 기법을 이용한 퍼지 제어기의 안정도 해석 (Stability Analysis of Fuzzy Control Systems via Convex Optimization)

  • 김은태;이희진
    • 전자공학회논문지CI
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    • 제38권6호
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    • pp.38-45
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    • 2001
  • 본 논문에서는 새로운 방식의 싱글톤 형태 퍼지 제어기의 안정도 해석 방식을 제안한다. 본 논문에서 제안되는 방식은 기존의 논문에서 찾을 수 있는 해석적 방식이 아니라 최적화 알고리즘을 이용한 수치적 접근 방식이다. 본 알고리즘은 크게 이차계획법과 선형 행렬 부등식으로 이루어져 있다. 끝으로 컴퓨터 모의 실험을 통해 타당성을 확인한다.

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Optimal Particle Swarm Based Placement and Sizing of Static Synchronous Series Compensator to Maximize Social Welfare

  • Hajforoosh, Somayeh;Nabavi, Seyed M.H.;Masoum, Mohammad A.S.
    • Journal of Electrical Engineering and Technology
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    • 제7권4호
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    • pp.501-512
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    • 2012
  • Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC.

Power Sharing and Cost Optimization of Hybrid Renewable Energy System for Academic Research Building

  • Singh, Anand;Baredar, Prashant
    • Journal of Electrical Engineering and Technology
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    • 제12권4호
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    • pp.1511-1518
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    • 2017
  • Renewable energy hybrid systems look into the process of choosing the finest arrangement of components and their sizing with suitable operation approach to deliver effective, consistent and cost effective energy source. This paper presents hybrid renewable energy system (HRES) solar photovoltaic, downdraft biomass gasifier, and fuel cell based generation system. HRES electrical power to supply the electrical load demand of academic research building sited in $23^{\circ}12^{\prime}N$ latitude and $77^{\circ}24^{\prime}E$ longitude, India. Fuzzy logic programming discover the most effective capital and replacement value on components of HRES. The cause regarding fuzzy logic rule usage on HOMER pro (Hybrid optimization model for multiple energy resources) software program finds the optimum performance of HRES. HRES is designed as well as simulated to average energy demand 56.52 kWh/day with a peak energy demand 4.4 kW. The results shows the fuel cell and battery bank are the most significant modules of the HRES to meet load demand at late night and early morning hours. The total power generation of HRES is 23,794 kWh/year to the supply of the load demand is 20,631 kWh/year with 0% capacity shortage.

불확실한 arc용량제약식들을 고려한 네트워크문제의 최적화 (Option of Network Flow Problem Considering Uncertain Arc Capacity Constraints)

  • 박주녕;송서일
    • 산업경영시스템학회지
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    • 제13권21호
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    • pp.51-60
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    • 1990
  • In this paper we deal with the miniaml cost network flow problem with uncertain arc capacity constraints. When the arc capacities are fuzzy with linear L-R type membership function, using parametric programming procedure, we reduced it to the deterministic minimal cost network flow problem which can be solved by various typical network flow algorithms. A modified Algorithm using the Out-of-kilter algorithm is developed.

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Apply evolved grey-prediction scheme to structural building dynamic analysis

  • Z.Y. Chen;Yahui Meng;Ruei-Yuan Wang;Timothy Chen
    • Structural Engineering and Mechanics
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    • 제90권1호
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    • pp.19-26
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    • 2024
  • In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.

퍼지 QFD를 활용한 공공부문 정보화 성과 측정범주 중요도 도출 (The Fuzzy QFD Approach to Importance the Public Sector Information Performance Measurement Category)

  • 오진석;송영일
    • 경영정보학연구
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    • 제12권2호
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    • pp.189-203
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    • 2010
  • 민간 및 정부 전 분야에 걸쳐서 정보화사업에 대해 많은 투자가 이루어지고 있으며, 이에 대한 투자대비 성과를 측정하고자 많은 노력들이 수행되고 있다. 정보화사업에 대한 평가는 크게 수준평가와 성과평가로 구분되고 있으며, 수준평가는 정부차원으로 매년 측정하고 성과평가는 자체 평가로 수행되고 있다. 공공부문에 있어서는 범정부 성과참조모델(Performance Reference Model: PRM) ver. 2.0이 개발되어 공통 참조모델로써 정보화 성과평가의 기준을 제시하고 있다. 범정부 PRM은 가장 근간이 되는 평가분류체계와 표준 가시경로 및 성과관리 표준 양식으로 구성되어 있으며, 이를 통해 성과요소들을 분류하고 인과관계를 정의하고 있다. 효율적인 정보화사업을 관리하기 위해서는 성과에 대한 평가를 객관적으로 할 수 있는 정량적인 수치화가 필요하다. 범정부 PRM은 평가분류체계에서 측정범주는 제공하고 있지만, 측정범주별 적용기준에 대한 상대적 중요도는 제시하지 못하고 있다. 이에 본 연구에서는 공공부문 정보화사업의 성과평가의 공통기준으로 적용되고 있는 범정부 PRM의 측정범주에 대한 중요도 평가 및 우선순위를 도출하고자 한다. 연구모형은 Fuzzy QFD (Quality Function Deployment)를 이용하였으며, 측정범주의 중요도 도출시 범정부 PRM의 개발목적을 잘 반영할 수 있도록 설계하였다. 전문가의 의견을 수렴함에 있어 불확실성과 모호성을 최소화시키기 위하여 퍼지이론을 접목한 Fuzzy AHP(Analytic Hierarchy Process)와 FPP(Fuzzy Preference Programming) 방법을 적용하였다. 범정부 PRM의 개발목적에서는 성과관리 참조모델로써의 가장 기본적인 요구사항이라 할 수 있는 "정보화 성과관리를 위한 표준모형 제공"이 가장 중요한 요소로 도출되고 있다. 측정범주에 서는 고객영역에서 "서비스 품질"이 가장 높은 우선순위를 보이고 있다. 정보시스템의 서비스에 대한 품질 관리 및 향상방안에 보다 많은 투자와 노력이 필요함을 엿볼 수 있다. 범정부 PRM의 측정범주에 대한 중요도는 정부 및 공공기관에 공통의 평가기준을 제공할 수 있으며, 이를 통해 자체 평가결과를 상호 비교하여 보완/발전시킬 수 있는 기회를 제공한다. 향후 연구시 성과분류체계의 구조모형에 대한 정량적인 인과관계를 규명한다면, 범정부 PRM은 보다 객관적이고 효율적인 참조모델로 발전할 수 있을 것이다.

The Impact of Redundancy and Teamwork on Resilience Engineering Factors by Fuzzy Mathematical Programming and Analysis of Variance in a Large Petrochemical Plant

  • Azadeh, Ali;Salehi, Vahid;Mirzayi, Mahsa
    • Safety and Health at Work
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    • 제7권4호
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    • pp.307-316
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    • 2016
  • Background: Resilience engineering (RE) is a new paradigm that can control incidents and reduce their consequences. Integrated RE includes four new factors-self-organization, teamwork, redundancy, and fault-tolerance-in addition to conventional RE factors. This study aimed to evaluate the impacts of these four factors on RE and determine the most efficient factor in an uncertain environment. Methods: The required data were collected through a questionnaire in a petrochemical plant in June 2013. The questionnaire was completed by 115 respondents including 37 managers and 78 operators. Fuzzy data envelopment analysis was used in different ${\alpha}$-cuts in order to calculate the impact of each factor. Analysis of variance was employed to compare the efficiency score means of the four abovementioned factors. Results: The results showed that as ${\alpha}$ approached 0 and the system became fuzzier (${\alpha}=0.3$ and ${\alpha}=0.1$), teamwork played a significant role and had the highest impact on the resilient system. In contrast, as ${\alpha}$ approached 1 and the fuzzy system went toward a certain mode (${\alpha}=0.9$ and ${\alpha}=1$), redundancy had a vital role in the selected resilient system. Therefore, redundancy and teamwork were the most efficient factors. Conclusion: The approach developed in this study could be used for identifying the most important factors in such environments. The results of this study may help managers to have better understanding of weak and strong points in such industries.