• Title/Summary/Keyword: 시스템 동정

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A Study on Development ATCS of Transfer Crane using Neural Network Predictive Control (신경회로망 예측제어에 의한 Transfer Crane의 ATCS 개발에 관한 연구)

  • 손동섭;이진우;이영진;이권순
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2002.11a
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    • pp.113-119
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    • 2002
  • Recently, an automatic crane control system is required with high speed and rapid transportation. During the operation of crane system in container yard it is necessary to control the crane trolley position and loop length so that the swing of the hanging container is minimized We can do development of unmanned automation control system using automation travel control technique and anti-sway technique in crane system. Therefore, we designed a controller for Automation travel control to control the transfer crane system. Analyzed crane system through simulation, and proved excellency of control performance than other conventional controllers.

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An Improvement of the Control Characteristics of Induction Motors using Adaptive Flux Observers (적응자속 업저버를 이용한 유도전동기의 제어특성 개선에 관한 연구)

  • 윤병도;박현호;김찬기
    • The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.8 no.4
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    • pp.46-54
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    • 1994
  • Exhbitlon hghting design be done aftrr due consideration of the photochermcal reaction and h ~ ~ i i tc~.fficits~ upn exposure to light. In this study the balanced judgement is as follows. The most light-susceptible material shouid be illu~stratrui less than 50[k] (illurnlnance-hours per year : 120, 000k.h)and the illuminance of moderately sensitive rriatcrinl k 200[1x] (illuminance hours per year : 480, 0001x.h). Moreover to minimize damage the sources of light shoulcl not only contribute as little as heat possible but remove ultraviolt radiation by filters. Also the sources of light must have good color rendering and low color temperature.

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Nonlinear Characteristics of Fuzzy Inference Systems by Means of Individual Input Space (개별 입력 공간에 의한 퍼지 추론 시스템의 비선형 특성)

  • Park, Keon-Jun;Lee, Dong-Yoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.11
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    • pp.5164-5171
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    • 2011
  • In fuzzy modeling for nonlinear process, typically using the given data, the fuzzy rules are formed by the input variables and the space division by selecting the input variable and dividing the input space for each input variables. The premise part of the fuzzy rule is identified by selection of the input variables, the number of space division and membership functions and the consequent part of the fuzzy rule is identified by polynomial functions in the form of simplified and linear inference. In general, formation of fuzzy rules for nonlinear processes using the given data have the problem that the number of fuzzy rules exponentially increases. To solve this problem complex nonlinear process can be modeled by separately forming the fuzzy rules by means of fuzzy division of each input space. Therefore, this paper utilizes individual input space to generate fuzzy rules. The premise parameters of the fuzzy rules are identified by Min-Max method using the minimum and maximum values of input data set and membership functions are used as a series of triangular, gaussian-like, trapezoid-type membership functions. And lastly, using the data which is widely used in nonlinear process we evaluate the performance and the system characteristics.

Influence of Dispersed and Anaerobic Bacteria in Aerobic Paper-making Wastewater Treatment (호기적 제지폐수 처리공정중에의 분산 혐기성 미생물의 영향)

  • 박종현;김선영;한완택
    • Microbiology and Biotechnology Letters
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    • v.28 no.3
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    • pp.180-184
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    • 2000
  • Tn order to be helpful to control dispersed microorganisms for stabLlization of wastewater treatment in a paper-makillg process, dominant strains were isolated aerobically and anaerobically. and identified and physiological characteristics were also analyzed. Pseudomonas carboxydohydrogena, Cardiobacten'm hominis, lvIicrococcus lylae, XanfomonCls campestris p" juglandis, Micrococcus diversus, and Comamonas terrigencl as aerobic dominants, and Streptococcus bovis and Prevotella buccae as anaerobIc dominants were identified fi'om the supernatent of the primary settling tank. It seemed that microflora in the treatment process would consist of many kinds of microorganisms, whose dominant would change easily according to environmental conditions, They all grew well at $37^{\circ}C$ and at different initial medium pH's. Especially, some of them required sulfate ion for their growth, which came from a chemical coagulant of aluminium sulfate in the primary settling tank. Interestingly. many anaerobes grew well even in the aerobic wastewater treatment process and seemed to have some functions. Population of anaerobes increased three times in the supematant of primary settling tank and ten times in Lhe bottom sludge of primary settling tank than in the prime wastewater. Therefore, these anaerobes contributed to the producH tion of offensive gases, which would make some microorganisms not precLpitate and be buoyant.

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A study of defects of filtered-X LMS algorithm for modeling error (모델링오차에 따른 Filtered-X LMS 알고리즘의 오동작에 관한 고찰)

  • Park Byoung-Uk;Ko Byeong-Seob;Kim Hack-Yoon
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.359-362
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    • 2000
  • ANC시스템에 있어서 현재 많이 이용되고있는 Filtered-X LMS 알고리즘에서 2차 음원과 제어점간의 임펄스응답은, 미리 동정하여 사용하는 것이 일반적이지만, 2차 음원과 제어점간의 전달특성이 이후에 변화할 경우, 실제의 전달함수와 적응에 이용한 전달함수간에 모델링 오차가 발생하게된다. 이 모델링 오차에 의하여 알고리즘은 오동작을 일으키고, 시스템은 불안정하게 되기도 한다. 따라서, 본 연구에서는 참조신호가 랜덤신호일 경우에 발생하는 모델링 오차와 Filtered-X LMS 알고리즘의 오동작에 관한 이론식을 도출하고, 시뮬레이션을 통하여 이를 입증하였다.

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Optimal Identification of Data Granules-based Genetically Optimized Fuzzy Relation Polynomial Neural Networks (데이터 입자 기반 유전론적 퍼지 관계 다항식 뉴럴네트워크의 최적 동정)

  • Lee In-Tae;Lee Young-Il;Oh Sung-Kwun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.11a
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    • pp.367-370
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    • 2005
  • 본 논문에서는 정보 입자화와 유전자 알고리즘을 기반으로 최적 퍼지 다항식 뉴럴네트워크를 제안하고, 유전자 알고리즘을 사용하여 종합적인 설계방법을 개발한다. 제안된 모델은 기존의 진화론적 퍼지 다항식 뉴럴네트워크의 구조를 정보입자화를 통해 좀 더 빠르게 최적의 해공간에 접근시키는데 그 목적이 있다. 퍼지 관계기반 다항식 뉴럴네트워크는 퍼지 다항식 뉴론이 기초가 되어 가능한 구조적이고 요소적으로 모델의 성능을 향상 시켜준다. 퍼지 다항식 뉴런의 최적 구조를 위해 유전자 알고리즘을 이용하여 입력변수의 수와 후반부 다항식의 차수 입력변수 수에 따른 입력변수 그리고 멤버쉽 함수의 수를 동조한다. 여기서, 클러스터링의 하나의 방법인 HCM에 의해 퍼지 규칙 각각의 전반부와 후반부에 데이터 중심값을 이용하여 다항식함수의 파라미터값을 결정한다. 제안된 유전론적 퍼지 관계 다항식 뉴럴네트워크의 성능평가는 기존 퍼지 모델링에서 이용된 표준 데이터를 활용하여 평가한다.

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Study on Flight Test Practice of the Small Civil Airplane Development for Pitot-Static System's Error Identification (소형 항공기 개발 동정압계통 오차 확인 비행시험 사례)

  • Kim, Chanjo;Seo, Jihan;Lee, Wonjoong
    • Journal of Aerospace System Engineering
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    • v.7 no.3
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    • pp.33-38
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    • 2013
  • The air data measured from the static pressure, the dynamic pressure and etc. of an airplane is used for calculation of many flight parameters(altitude and airspeed and so on) and these values applied to flight safety and navigation flight. The pitot-static system of the development airplane is calibrated by finding of pitot-static system's error using tower fly-by, trailing cone method and etc. This paper is describing for the introduction of the trailing cone method and major items for test planning, preparation, operation and results for air data calibration flight test performed, considering efficiency and safety during KC-100 development project.

Fuzzy identification by means of fuzzy inference method (퍼지추론 방법에 의한 퍼지동정)

  • 안태천;황형수;오성권;김현기;우광방
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.200-205
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    • 1993
  • A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type 1), linear inference (type 2), and modified linear inference (type 3). The fuzzy c-means clustering and modified complex methods are used in order to identify the preise structure and parameter of fuzzy implication rules, respectively and the least square method is utilized for the identification of optimal consequence parameters. Time series data for gas funace and sewage treatment processes are used to evaluate the performances of the proposed rule-based fuzzy modeling.

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Fuzzy Rule Identification Using Messy Genetic Algorithm (메시 유전 알고리듬을 이용한 퍼지 규칙 동정)

  • Kwon, Oh-Kook;Chang, Wook;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.10a
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    • pp.252-256
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    • 1997
  • The success of a fuzzy neural network(FNN) control system solving any given problem critically depends on the architecture of the network. Various attempts have been made in optimizing its structure using genetic algorithm automated designs. This paper presents a new approach to structurally optimized designs of FNN models. A messy genetic algorithm is used to obtain structurally optimized FNN models. Structural optimization is regarded important before neural networks based learning is switched into. We have applied the method to the problem of a numerical approximation

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The Architecture and Identification Algorithm of Self-Organizing Polynomial Neural Networks by GAs (유전자 알고리즘에 의한 자기구성 다항식 뉴럴 네트워크의 구조 및 동정 알고리즘)

  • 박호성;오성권
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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    • pp.434-437
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    • 2004
  • 본 논문에서는 유전자 알고리즘에 기반을 둔 자기구성 다항식 뉴럴네트워크(Self-Organizing Polynomial Neural Networks: SOPNN)의 새로운 구조를 제안하고, 포괄적인 설계 방법론을 토의한다. 기존의 자기구성 다항식 뉴럴 네트워크는 확장된 GMDH 방법에 기반을 두며, 네트워크의 성장과정을 통하여 각 충의 다항식 뉴런에서 고정된 노드 입력들의 수 뿐만 아니라 다항식 차수(1차, 2차, 그리고 수정된 2차식)를 이용하였다. 더구나, 그 방법은 학습을 통해 생성된 SOPNN이 최적 네트워크 구조를 가진다는 것을 보증하지 못한다. 그러나, 제안된 GA 기반 SOPNN은 그 구조를 구조적으로 더 최적화된 네트워크가 되도록 하고, 기존의 SOPNN보다 훨씬 더 유연하고, 선호된 뉴럴 네트워크가 되도록 한다. 구조적으로 더 최적화된 SOPNN을 생성하기 위해, SOPNN의 각 단계에서의 GA기반 설계 절차는 SOPNN내에서 이용할 수 있는 다음의 최적 파라미터들- 즉 입력변수의 수, 입력변수, 및 다항식 차수-을 가진 선호된 노드들의 선택으로 이끈다. 하중계수를 가진 합성성능지수가 그 모델의 근사화 및 일반화(예측) 능력 사이의 상호 균형을 얻기 위해 제안된다. 상세 설계 절차가 상세히 토의된다.

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