• Title/Summary/Keyword: Fuzzy control rules

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Modeling the Distribution Demand Estimation for Urban Rail Transit (퍼지제어를 이용한 도시철도 분포수요 예측모형 구축)

  • Kim, Dae-Ung;Park, Cheol-Gu;Choe, Han-Gyu
    • Journal of Korean Society of Transportation
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    • v.23 no.2
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    • pp.25-36
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    • 2005
  • In this study, we suggested a new approach method forecasting distribution demand of urban rail transit usign fuzzy control, with intend to reflect irregularity and various functional relationship between trip length and distribution demand. To establish fuzzy control model and test this model, the actual trip volume(production, attraction and distribution volume) and trip length (space distance between a departure and arrival station) of Daegu subway line 1 were used. Firstly, usign these data we established a fuzzy control model, nd the estimation accuracy of the model was examined and compared with that of generalized gravity model. The results showed that the fuzzy control model was superior to gravity model in accuracy of estimation. Therefore, wwe found that fuzzy control was able to be applied as a effective method to predict the distribution demand of urban rail transit. Finally, to increase the estimation precision of the model, we expect studies that define membership functions and set up fuzzy rules organized with neural networks.

Design and Performance evaluation of Fuzzy-based Framed Random Access Controller ($F^2RAC$) for the Integration of Voice ad Data over Wireless Medium Access Control Protocol (프레임 구조를 갖는 무선 매체접속제어 프로토콜 상에서 퍼지 기반의 음성/데이터 통합 임의접속제어기 설계 및 성능 분석)

  • 홍승은;최원석;김응배;강충구;임묘택
    • Proceedings of the IEEK Conference
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    • 2000.11a
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    • pp.189-192
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    • 2000
  • This paper proposes a fuzzy-based random access controller with a superimposed frame structure (F$^2$RAC) fur voice/data-integrated wireless networks. F$^2$RAC adopts mini-slot technique for reducing contention cost, and these mini-slots of which number may dynamically vary from one frame to the next as a function of the traffic load are further partitioned into two regions for access requests coming from voice and data traffic with their respective QoS requirements. And F$^2$RAC is designed to properly determine the access regions and permission probabilities for enhancing the data packet delay while ensuring the voice packet dropping probability constraint. It mainly consists of the estimator with Pseudo-Bayesian algorithm and fuzzy logic controller with Sugeno-type of fuzzy rules. Simulation results prove that F$^2$RAC can guarantee QoS requirement of voice and provide the highest throughput efficiency and the smallest data packet delay amongst the different alternatives including PRMA[1], IPRMA[2], and SIR[3].

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Design and evaluation of an alert message dissemination algorithm using fuzzy logic for VANETs

  • Bae, Ihn-Han
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.4
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    • pp.783-793
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    • 2010
  • Several multi-hop applications developed for vehicular ad hoc networks use broadcast as a means to either discover nearby neighbors or propagate useful traffic information to other vehicles located within a certain geographical area. However, the conventional broadcast mechanism may lead to the so-called broadcast storm problem, a scenario in which there is a high level of contention and collisions at the link layer due to an excessive number of broadcast packets. We present a fuzzy alert message dissemination algorithm to improve performance for road safety alert application in Vehicular Ad-hoc Network (VANET). In the proposed algorithm, when a vehicle receives an alert message for the first time, the vehicle rebroadcasts the alert message according to the fuzzy control rules for rebroadcast degree, where the rebroadcast degree depends on the current traffic density of the road and the distance between source vehicle and destination vehicle. Also, the proposed algorithm is the hybrid algorithm that uses broadcast protocol together with token protocol according to traffic density. The performance of the proposed algorithm is evaluated through simulation and compared with that of other alert message dissemination algorithms.

Development of Combustion Diagnostic System for Reducing the Exhausting Gas (배기가스 저감을 위한 연소진단 시스템의 개발)

  • Lee, Tae-Young
    • Journal of the Korean Society of Industry Convergence
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    • v.4 no.4
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    • pp.403-411
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    • 2001
  • A criterion for evaluation of burners has changed recently, and the environmental problems are raised as a global issue. Burners with higher thermal efficiency and lower oxygen in the exhaust gas, evaluated better. To comply with environmental regulations, burners must satisfy the $NO_x$ and CO regulation. Consequently. 'good burner' means one whose thermal efficiency is high under the constraint of $NO_x$ and CO consistency. To make existing burner satisfy recent criterion, it is highly recommended to develop a feedback control scheme whose output is the consistency of $NO_x$ and CO. This paper describes the development of a real time flame diagnosis technique that evaluate and diagnose the combustion states, such as consistency of components in exhaust gas, stability of flame in the quantitative sense. In this paper, it was proposed on the flame diagnosis technique of burner using Neuro- Fuzzy algorithm. This study focuses on the relation of the color of the flame and the state of combustion. Neuro- Fuzzy learning algorithm is used in obtaining the fuzzy membership function and rules. Using the constructed inference algorithm, the amount of $NO_x$ and CO of the combustion gas was successfully inferred.

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Automatic generation of Fuzzy Parameters Using Genetic and gradient Optimization Techniques (유전과 기울기 최적화기법을 이용한 퍼지 파라메터의 자동 생성)

  • Ryoo, Dong-Wan;La, Kyung-Taek;Chun, Soon-Yong;Seo, Bo-Hyeok
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.515-518
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    • 1998
  • This paper proposes a new hybrid algorithm for auto-tuning fuzzy controllers improving the performance. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a genetic-MGM algorithm. The object of the proposed algorithm is to promote search efficiency by a genetic and modified gradient optimization techniques. The proposed genetic and MGM algorithm is based on both the standard genetic algorithm and a gradient method. If a maximum point don't be changed around an optimal value at the end of performance during given generation, the genetic-MGM algorithm searches for an optimal value using the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algorithms. Simulation results verify the validity of the presented method.

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Design of a NeuroFuzzy Controller for the Integrated System of Voice and Data Over Wireless Medium Access Control Protocol (무선 매체 접근 제어 프로토콜 상에서의 음성/데이타 통합 시스템을 위한 뉴로 퍼지 제어기 설계)

  • Choi, Won-Seock;Kim, Eung-Ju;Kim, Beom-Soo;Lim, Myo-Taeg
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.1990-1992
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    • 2001
  • In this paper, a NeuroFuzzy controller (NFC) with enhanced packet reservation multiple access (PRMA) protocol for QoS-guaranteed multimedia communication systems is proposed. The enhanced PRMA protocol adopts mini-slot technique for reducing contention cost, and these minislot are futher partitioned into multiple MAC regions for access requests coming from users with their respective QoS (quality-of-service) requirements. And NFC is designed to properly determine the MAC regions and access probability for enhancing the PRMA efficiency under QoS constraint. It mainly contains voice traffic estimator including the slot information estimator with recurrent neural networks (RNNs) using real-time recurrent learning (RTRL), and fuzzy logic controller with Mandani- and Sugeno-type of fuzzy rules. Simulation results show that the enhanced PRMA protocol with NFC can guarantee QoS requirements for all traffic loads and further achieves higher system utilization and less non real-time packet delay, compared to previously studied PRMA, IPRMA, SIR, HAR, and F2RAC.

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The Optimization of Fuzzy Logic Controllers Using Genetic Algorithm (유전 알고리듬을 이용한 퍼지 제어기의 최적화)

  • Chang, Wook;Park, Jin-Bae;Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.4
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    • pp.48-57
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    • 1997
  • This paper presents the automatic construction and parameter optimization technique for fuzzy logic controllers using genetic algorithm. In general. the design of fuzzy logic controllers has difficulties in the acq~lisition of expert's knowledge and relies to a great extent on empirical and heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controllers c:an be degraded in the case of plant parameter variations or unpredictable incident which a designer may have ignored, and the parameters of fuzzy logic controllers obtained by expert's control action may not be optirnal. Some of these problems can be resolved by the use of genetic algorithm. The proposed method can tune the parameters of fuzzy logic controllers including scaling factors and determine: the appropriate number of fuzzy rulcs systematically. Finally, we provides the second order dead time plant to evaluate the feasibility and generality of the proposed method. Comparison shows that the proposed method can produce fuzzy logic controllers with higher accuracy and a smaller number of fuzzy rules than manually tuned fuzzy logic controllers.

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T-S Fuzzy Modeling for Container Cranes Using a RCGA Technique (RCGA 기법을 이용한 컨테이너 크레인의 T-S 퍼지 모델링)

  • Lee, Yun-Hyung;Yoo, Heui-Han;Jung, Byung-Gun;So, Myung-Ok;Jin, Gang-Gyoo;Oh, Sea-June
    • Journal of Navigation and Port Research
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    • v.31 no.8
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    • pp.697-703
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    • 2007
  • In this paper, we focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. A T-S fuzzy model is characterized by fuzzy "if-then" rules which represent the locally input-output relationship whose consequence part is described by a state space equation as subsystem. The T-S fuzzy model in container cranes first obtains a few number of linear models according to operation conditions and blends these conditions using fuzzy membership functions. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear system of a container crane. Simulations are given to illustrate the performance of T-S fuzzy model.

Design and Evaluation of a Fuzzy Logic-based Selective Paging Method for Wireless Mobile Networks (무선 이동망을 위한 퍼지 논리 기반 선택적 페이징 방법의 설계 및 평가)

  • 배인한
    • Journal of KIISE:Information Networking
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    • v.31 no.3
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    • pp.289-297
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    • 2004
  • State-of-the-art wireless communication networks allow dynamic relocation of mobile terminals. A location management mechanism is required to keep track of a mobile terminal for delivering incoming calls. In this paper, we propose a fuzzy logic-based selective paging method to reduce paging cost. In the proposed fuzzy logic-based location management method, the location update uses the area-based method that uses direction-based together with movement-based methods, and the location search uses the fuzzy logic-based selective paging method based on the mobility information of mobile terminals. A partial candidate paging area is selected by fuzzy control rules, then the fuzzy logic-based selective paging method pages only the cells within the partial candidate paging area. The performance of proposed fuzzy logic-based location management method is to be evaluated by both an analytical model and a simulation, and is compared with those of LA and BVP methods. From these evaluation results, we know that the proposed fuzzy logic-based location management method provide better performance than other location management methods.

Analysis of Steady State Error on Simple FLC (단순 FLC의 정상상태오차 해석)

  • Lee, Kyoung-Woong;Choi, Han-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.9
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    • pp.897-901
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    • 2011
  • This paper presents a TS (Takagi-Sugeno) type FLC (Fuzzy Logic Controller) with only 3 rules. The choice of parameters of FLC is very difficult job on design FLC controller. Therefore, the choice of appropriate linguistic variable is an important part of the design of fuzzy controller. However, since fuzzy controller is nonlinear, it is difficult to analyze mathematically the affection of the linguistic variable. So this choice is depend on the expert's experience and trial and error method. In the design of the system, we use a variety of response characteristics like stability, rising time, overshoot, settling time, steady-state error. In particular, it is important for a stable system design to predict the steady-state error because the system's steady-state response of the system is related to the overall quality. In this paper, we propose the method to choose the consequence linear equation's parameter of T-S type FLC in the view of steady-state error. The parameters of consequence linear equations of FLC are tuned according to the system error that is the input of FLC. The full equation of T-S type FLC is presented and using this equation, the relation between output and parameters can represented. As well as the FLC parameters of consequence linear equations affect the stability of the system, it also affects the steady-state error. In this study, The system according to the parameter of consequence linear equations of FLC predict the steady-state error and the method to remove the system's steady-state error is proposed using the prediction error value. The simulation is carried out to determine the usefulness of the proposed method.