• Title/Summary/Keyword: Adaptive Rule

검색결과 266건 처리시간 0.023초

비선형 함수의 분해를 이용한 퍼지시스템의 재구성과 퍼지규칙수 줄임 알고리즘 (Fuzzy Rule Reduction Algorithms and the Reconstruction of Fuzzy System using Decomposition of Nonlinear Functions)

  • 유병국
    • 융합신호처리학회논문지
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    • 제2권2호
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    • pp.95-102
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    • 2001
  • 일반적으로 피지시스템은 compact한 공간에 대한 어떠한 비선형 함수도 일정오차 이내에서 근사할 수 있다. 그러나 퍼지시스템의 응용은 퍼지규칙의 수가 많아지는 경우, 특히 고차의 비선형 시스템에 대하여는 사용되기 어렵다는 단점을 가지고 있다. 본 논문에서는 근사하고자 하는 비선형 함수의 분해를 이용한, 병렬형과 종속형의 두 가지 형태의 퍼지시스템 재구성 방식을 제안한다. 이 두 가지 형태의 재구성을 적절히 이용하여 퍼지규칙의 수를 기하급수적으로 줄일 수 있다. 제안된 알고리즘은 적응구조를 가진 퍼지시스템에 대하여 응용 가능하며 두 가지 적웅 퍼지 슬라이딩제어 예를 통하여 그 타당성을 보인다.

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유도전동기 드라이브의 고성능 제어를 위한 적응 FNN 제어기 (Adaptive FNN Controller for High Performance Control of Induction Motor Drive)

  • 이정철;이홍균;정동화
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제53권9호
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    • pp.569-575
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    • 2004
  • This paper is proposed adaptive fuzzy-neural network(FNN) controller for high performance of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control Performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation. and steady- state accuracy and transient response.

A Design for Elevator Group Controller of Building Using Adaptive Dual Fuzzy Algorithm

  • Kim, Hun-Mo
    • Journal of Mechanical Science and Technology
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    • 제15권12호
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    • pp.1664-1675
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    • 2001
  • In this paper, the development of a new group controller for high-speed elevators is described utilizing the approach of adaptive dual fuzzy logic. Some goals of the control are to minimize the waiting time, mean-waiting time and long-waiting time in a building. When a new hall call is generated, all adaptive dual fuzzy controller evaluates the traffic patterns and changes the membership function of a fuzzy rule base appropriately. A control algorithm is essential to control the cooperation of multiple elevators in a group and the most critical control function in the group controller is an effective and proper hall call assignment of the elevators. The group elevator system utilizing adaptive dual fuzzy control clearly performs more effectively than previous group controllers.

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공정제어를 위한 퍼지 적응제어기의 설계 (The Design of a Fuzzy Adaptive Controller for the Process Control)

  • Lee Bong Kuk
    • 전자공학회논문지B
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    • 제30B권7호
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    • pp.31-41
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    • 1993
  • In this paper, a fuzzy adaptive controller is proposed for the process with large delay time and unmodelled dynamics. The fuzzy adaptive controller consists of self tuning controller and fuzzy tuning part. The self tuning controller is designed with the continuous time GMV (generalized minimum variance) using emulator and weighted least square method. It is realized by the hybrid method. The controller has robust characteristics by adapting the inference rule in design parameters. The inference processing is tuned according to the operating point of the process having the nonlinear characteristics considering the practical application. We review the characteristics of the fuzzy adaptive controller through the simulation. The controller is applied to practical electric furnace. As a result, the fuzzy adaptive controller shows the better characteristics than the simple numeric self tuning controller and the PI controller.

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클래스간의 거리를 고려한 학습법칙을 사용한 퍼지 신경회로망 모델 (Fuzzy Neural Network Model Using A Learning Rule Considering the Distances Between Classes)

  • 김용수;백용선;이세열
    • 한국지능시스템학회논문지
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    • 제16권4호
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    • pp.460-465
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    • 2006
  • 본 논문은 입력 벡터와 클래스들의 대표값들간의 유클리디안 거리들을 사용한 새로운 퍼지 학습법칙을 제안한다. 이 새로운 퍼지 학습을 supervised IAFC(Integrated Adaptive Fuzzy Clustering) 신경회로망 4에 적용하였다. 이 신경회로망은 안정성을 유지하면서도 유연성을 가지고 있다. iris 데이터를 사용하여 테스트한 결과 supervised IAFC 신경회로망 4는 오류역전파 신경회로망과 LVQ 알고리듬보다 성능이 우수하였다.

수리형학과 적응적 종료 규칙을 이용한 영상 복원 (An iterative restoration algorithm using adaptive termination rule and mathematical morphology)

  • 김인겸;이두현;송홍엽;박규태
    • 전자공학회논문지B
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    • 제33B권7호
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    • pp.116-126
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    • 1996
  • In this paper, we propose a new termination rule for the iterative restoration of degraded images, by which the number of iterations can be dramatically reduced. This rule uses a parameter, called noise suppression factor (NSF), to appropriately teminate the iteration process, reduces a lot the computational load, and avoids the amplification of noise for the better quality. We also propose a method using the morphological filters, when applied to the resulting image, that will significantly reduce the ringing effect which would otherwise exist in the boundary of the image. Simulation with the blurred lena image with gaussian noise showns that the proposed termination rule combined with the morphological filtering gives the restored image with much improved quality.

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Optimum Uplink Power/Rate Control for Minimum Delay in CDMA Networks

  • Choi, Kwon-Hue;Kim, Soo-Young
    • ETRI Journal
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    • 제25권6호
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    • pp.437-444
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    • 2003
  • We derive a new joint power and rate control rule with which we can minimize the mean transmission delay in CDMA networks for a given mean transmission power. We show that it is optimal to respectively control the power inverse-linearly and the rate linearly to the square root of channel gain while maintaining the signal-to-interference ratio at a constant. We also show that the proposed joint power/rate control rule achieves excellent performance results in terms of the probability of the instantaneous delay being within a target delay against one-dimensional control schemes.

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신경망을 이용한 적응제어기의 추적 성능 평가 (Tracking performance evaluation of adaptive controller using neural networks)

  • 최수열;박재형;박선국
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.1561-1564
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    • 1997
  • In the study, simulation result was studied by connecting PID controller in series to the established Neural Networks Controller. Neural Network model is composed of two layers to evaluate tracking performance improvement. The reqular dynamic characteristics was also studied for the expected error to be minimized by using Widrow-Hoff delta rule. As a result of the study, We identified that tracking performance inprovement was developed more in case of connecting PID than Neural Network Contoller and that tracking plant parameter in 251 sample was approached rapidly case of time variable.

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확장된 퍼지엔트로피 클러스터링을 이용한 카오스 시계열 데이터 예측 (Chaotic Time Series Prediction using Extended Fuzzy Entropy Clustering)

  • 박인규
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 하계종합학술대회 논문집(3)
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    • pp.5-8
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    • 2000
  • In this paper, we propose new algorithms for the partition of input space and the generation of fuzzy control rules. The one consists of Shannon and extended fuzzy entropy function, the other consists of adaptive fuzzy neural system with back propagation teaming rule. The focus of this scheme is to realize the optimal fuzzy rule base with the minimal number of the parameters of the rules, reducing the complexity of the system. The proposed algorithm is tested with the time series prediction problem using Mackey-Glass chaotic time series.

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에탄올 생산을 위한 세포재순환 연속 생물반응기의 적응제어 (Adaptive Control of Cell Recycled Continuous Bioreactor for Ethanol Production)

  • 이재우;유영제
    • KSBB Journal
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    • 제6권3호
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    • pp.263-270
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    • 1991
  • The optimal cell concentration and dilution rate for maximum ethanol productivity were obtained using dynamic simulation in cell recycled continuous bioreactor. The good control performance was observed using rule-based STR (self-tuning regulator) compared to conventional STR. Rule-base contained the scheme to implement the STR in an efficient on-off way and the scheme for the controlled variable to reach the optimal value in a short time. Since a mathematical model was used to analyze and estimate the changes of the state variables and the parameters, it was possible to understand the physical meaning of the system.

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