• 제목/요약/키워드: multiple fuzzy systems

검색결과 253건 처리시간 0.028초

후판 압연공정에서 퍼지 두께제어 구현 (An Implementation of Fuzzy Automatic Gauge Control for the Plate Steel Rolling Process)

  • 허윤기;최영규
    • 제어로봇시스템학회논문지
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    • 제15권6호
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    • pp.634-640
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    • 2009
  • The plate manufacturing processes are composed of the reheating furnace, finishing mill, cooling process and hot leveling. The finishing rolling mill (FM) as a reversing mill has produced the plate steel through multiple pass rolling. The automatic gauge control (AGC) is employed to maintain the thickness tolerance. The high grade products are forming greater parts of the manufacturing and customers are requiring strict thickness margin. For this reason, the advanced AGC method is required instead of the conventional AGC based on the PI control. To overcome the slow response performance of the conventional AGC and the thickness measurement delay, a fuzzy AGC based on the thickness deviation and its trend is proposed in this paper. An embedded controller with the fuzzy AGC has been developed and implemented at the plate mill in POSCO. The fuzzy AGC has dynamically controlled the roll gap in real time with the programmable logic controller (PLC). On line tests have been performed for the general and TMCP products. As the results, the thickness deviation range (maximum - minimum of the inner plate) is averagely from 0.3 to 0.1 mm over the full length. The fuzzy AGC has improved thickness deviation and completely satisfied customer needs.

퍼지 칼만 필터를 이용한 새로운 지능형 추적 알고리즘 (A New Intelligent Tracking Algorithm Using Fuzzy Kalman Filter)

  • 노선영;주영훈;박진배
    • 한국지능시스템학회논문지
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    • 제15권5호
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    • pp.593-598
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    • 2005
  • 표적의 상태를 추정하기 위해 사용된 칼만 필터는 급 기동을 하거나 비선형적인 운동특성을 가지는 표적이 발생할 때, 모델은 상당한 오차를 유발하며 추적 성능은 현저히 저하될 수 있다. 이러한 문제점을 해결하기 위해서 본 논문에서는 기동하는 표적을 추정하기 위한 새로운 지능형 추정 알고리즘을 제안한다. 제안된 알고리즘은 유전 알고리즘에 기반한 퍼지 칼만 필터를 이용하여 실제 알지 못하는 표적의 가속도를 전체 프로세스 잡음으로 추정한 후, 보정된 필터의 잔여치와 변화를 이용한 퍼지 시스템으로 새로운 퍼지 이득을 추출하여 측정 예측 오차를 보정함으로써 한 개의 필터로 표적 움직임의 비선형성을 효과적으로 다룰 수 있다. 제안된 기법의 우수성을 검증하기 위해서 다중 모델 기법을 사용한 필터와 비교 모의실험을 하였다.

계층적구조를 갖는 시스템의 FUZZY GOALS에 관한 연구 (A study on fuzzy goals of system with hierarchical structure)

  • 박주녕;송서일
    • 산업경영시스템학회지
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    • 제12권20호
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    • pp.97-104
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    • 1989
  • 본 연구는 계층구조를 갖는 시스템의 각 목적함수들에 퍼지(FUZZY)집합 개념을 적용한 이단계 선형계획 모형을 다목적계획법으로 다루었다. 선형멤버쉽 함수를 이용하여 전형적인 Bi-level Linear Programming Problem(BLPP)으로 변형시켰으며, 기존의 BLPP 해법을 이용한 변형된 해법을 주시하고 예제를 통한 계산결과를 제시하였다. 퍼지이단계선형계층 (FBLPP)은 BLPP보다 실제환경을 자연스럽게 묘사할 수 있다. FBLPP는 각 의사결정자가 다목적함수를 갖는 다목적 이단계수리계획 모형의 유효해를 구하는데 이용할 수 있다.

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지능제어기를 이용한 자율 이동로봇의 운항 (Navigation of Autonomous Mobile Robot with Intelligent Controller)

  • 최정원;김연태;이석규
    • 한국지능시스템학회논문지
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    • 제13권2호
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    • pp.180-185
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    • 2003
  • 본 논문은 장애물에 대한 사전 정보를 가지고 있지 않은 공간에서 장애물의 회피와 지정된 목표점으로 이동할 수 있는 자율이동로봇을 위한 지능제어 알고리즘을 제안하고, 제안된 제어기의 효용성을 실험을 통하여 검증을 한다. 제시하는 지능 제어기는 계층구조의 알고리즘으로써, 그 하부에 로봇이 목표에 도달하기 위한 퍼지 알고리즘과 주행 중 만날 수 있는 장애물들에 대한 회피를 수행하는 퍼지-뉴럴 알고리즘이 존재하고, 상부의 가중치 퍼지 알고리즘은 로봇이 이동하면서 만날 수 있는 여러 가지 상황에 따라서 하부의 두 알고리즘에 적당한 가중치를 부여하여 장애물 회피동작과 목표점 도달동작을 수행할 수 있도록 구성되어 있다. 그리고 로봇의 현재 운동정보와 장애물까지의 거리정보를 바탕으로 가중치 퍼지 알고리즘의 출력부 소속도 함수를 조절함으로서 오목한 장애물에 대해서도 장애물 회피 동작을 수행하도록 하였다. 제작된 로봇으로 제시한 알고리즘의 실효성을 검증하였다.

Multiobjective Genetic Algorithm for Scheduling Problems in Manufacturing Systems

  • Gen, Mitsuo;Lin, Lin
    • Industrial Engineering and Management Systems
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    • 제11권4호
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    • pp.310-330
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    • 2012
  • Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

Fast Evolution by Multiple Offspring Competition for Genetic Algorithms

  • Jung, Sung-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제10권4호
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    • pp.263-268
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    • 2010
  • The premature convergence of genetic algorithms (GAs) is the most major factor of slow evolution of GAs. In this paper we propose a novel method to solve this problem through competition of multiple offspring of in dividuals. Unlike existing methods, each parents in our method generates multiple offspring and then generated multiple offspring compete each other, finally winner offspring become to real offspring. From this multiple offspring competition, our GA rarel falls into the premature convergence and easily gets out of the local optimum areas without negative effects. This makes our GA fast evolve to the global optimum. Experimental results with four function optimization problems showed that our method was superior to the original GA and had similar performances to the best ones of queen-bee GA with best parameters.

Handover in LTE networks with proactive multiple preparation approach and adaptive parameters using fuzzy logic control

  • Hussein, Yaseein Soubhi;Ali, Borhanuddin M;Rasid, Mohd Fadlee A.;Sali, Aduwati
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권7호
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    • pp.2389-2413
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    • 2015
  • High data rates in long-term evolution (LTE) networks can affect the mobility of networks and their performance. The speed and motion of user equipment (UE) can compromise seamless connectivity. However, a proper handover (HO) decision can maintain quality of service (QoS) and increase system throughput. While this may lead to an increase in complexity and operational costs, self-optimization can enhance network performance by improving resource utilization and user experience and by reducing operational and capital expenditure. In this study, we propose the self-optimization of HO parameters based on fuzzy logic control (FLC) and multiple preparation (MP), which we name FuzAMP. Fuzzy logic control can be used to control self-optimized HO parameters, such as the HO margin and time-to-trigger (TTT) based on multiple criteria, viz HO ping pong (HOPP), HO failure (HOF) and UE speeds. A MP approach is adopted to overcome the hard HO (HHO) drawbacks, such as the large delay and unreliable procedures caused by the break-before-make process. The results of this study show that the proposed method significantly reduces HOF, HOPP, and packet loss ratio (PLR) at various UE speeds compared to the HHO and the enhanced weighted performance HO parameter optimization (EWPHPO) algorithms.

Optimal Electric Energy Subscription Policy for Multiple Plants with Uncertain Demand

  • Nilrangsee, Puvarin;Bohez, Erik L.J.
    • Industrial Engineering and Management Systems
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    • 제6권2호
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    • pp.106-118
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    • 2007
  • This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

Response and control of jacket structure with magneto-rheological damper at multiple locations/combinations

  • Syed, Khaja A.A.;Kumar, Deepak
    • Ocean Systems Engineering
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    • 제8권2호
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    • pp.201-221
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    • 2018
  • In this paper a comprehensive study for the structural control of Jacket platform with Magneto-Rheological (MR) damper is presented. The control is implemented as a closed loop feedback of the applied voltage in the MR Damper using fuzzy logic. Nine cases of combinations with MR damper are presented to complete the work. The selection of the MR damper (RD 1005-3) is based on the operating parameters (i.e., the range of frequency and displacement). Bingham model is used to obtain the control forces. The damping co-efficient of the model is obtained using empirical relationship between the voltage in the MR damper and input velocity from the structural members. The force acting on the structure is obtained from Morison equation using P-M spectrum. The results show that the reliable control was obtained when there was a continuous connection of multiple MR dampers with the lower levels of the structure. Independent MR dampers at different levels provided control within a range, while the MR dampers placed at alternate positions gave very high control.

러프 집합 기반 적응 모델 선택을 갖는 다중 모델 퍼지 예측 시스템 구현과 시계열 예측 응용 (Multiple Model Fuzzy Prediction Systems with Adaptive Model Selection Based on Rough Sets and its Application to Time Series Forecasting)

  • 방영근;이철희
    • 한국지능시스템학회논문지
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    • 제19권1호
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    • pp.25-33
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    • 2009
  • 최근 시계열 예측에 결론부에 선형식을 갖는 TS 퍼지 모델이 많이 이용되고 있는데, 이의 예측 성능은 정상성과 같은 데이터의 특성과 밀접한 관련이 있다. 그러므로 본 논문에서는 특히 비정상 시계열 예측에 매우 효과적인 새로운 예측 기법을 제안하였다. 시계열의 패턴이나 규칙성을 잘 끌어내기 위한 데이터 전처리 과정을 도입하고 다중 모델 TS 퍼지 예측기를 구성한 뒤, 러프집합을 이용한 적응 모델 선택 기법에 의해 입력 데이터의 특성에 따라 가변적으로 적합한 예측 모델을 선택하여 시계열 예측이 수행되도록 하였다. 마지막으로 예측 오차를 감소시키기 위하여 오차 보정 메커니즘을 추가함으로써 예측 성능을 더욱 향상시켰다. 시뮬레이션을 통해 제안된 기법의 성능을 검증하였다. 제안된 기법은 예측 모델 구현과 예측 수행 과정에서 시계열 데이터의 특성들을 잘 반영할 수 있으므로 불확실성과 비정상성을 갖는 시계열의 예측에 매우 효과적으로 이용될 수 있을 것이다.