• 제목/요약/키워드: D-fuzzy filter

검색결과 20건 처리시간 0.022초

e-FUZZY FILTERS OF MS-ALGEBRAS

  • Alaba, Berhanu Assaye;Alemayehu, Teferi Getachew
    • Korean Journal of Mathematics
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    • 제27권4호
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    • pp.1159-1180
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    • 2019
  • In this article, we present the notion of e-fuzzy filters in an MS-Algebra and characterize in terms of equivalent conditions. The concept of D-fuzzy filters is studied and the set of equivalent conditions under which every e-fuzzy filter is an D-fuzzy filter are observed. Moreover we study some properties of the space of all prime e-fuzzy filters of an MS-algebra.

영상 잡음 제거 필터를 위한 퍼지 순환 신경망 연구 (A study on the Fuzzy Recurrent Neural Networks for the image noise elimination filter)

  • 변오성
    • 한국컴퓨터정보학회논문지
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    • 제16권6호
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    • pp.61-70
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    • 2011
  • 본 논문은 퍼지를 적용한 순환 신경망을 이용하여 잡음 제거용 필터를 구현하였다. 제안된 퍼지 순환 신경망 구조는 기본적으로 순환 신경망 구조를 이용하여 가중치 및 반복횟수가 일정한 값에 수렴하도록 하였으며, 하이브리드 퍼지 소속 함수 연산자를 적용하여 수학적인 계산량 및 복잡성를 단순화하였다. 본 논문은 제안된 퍼지 순환 신경망 구조 필터가 일반적인 순환 신경망 구조 필터보다 평균 0.38dB 정도 영상복원이 개선됨을 PSNR을 이용하여 증명하였다. 또한 결과 영상 비교에서 제안된 방법을 적용하여 얻은 영상이 기존 방법을 적용하여 얻은 영상보다 원영상과 더 유사함을 확인하였다.

기동 표적 추적을 위한 유전알고리즘 기반 퍼지 모델링 기법 (GA based fuzzy modeling method for tracking a maneuvering target)

  • 노선영;이범직;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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    • pp.2702-2704
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    • 2005
  • This paper proposes the genetic algorithm (GA)-based fuzzy modeling method for intelligent tracking of a maneuvering target. When the maneuvering to turn or taking evasive action, the performance of the standard Kalman filter has been degraded because residual between the modeled target dynamics and the actual target dynamics. To solve this problem, the state prediction error is minimized by the intelligent estimation method. Then, this filter is corrected by measurement corrections which is the fuzzy system. The performance of the proposed method is compared with those of the input estimation(IE) technique through computer simulation.

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Harmonic Mitigation and Power Factor Improvement using Fuzzy Logic and Neural Network Controlled Active Power Filter

  • Kumar, V.Suresh;Kavitha, D.;Kalaiselvi, K.;Kannan, P. S.
    • Journal of Electrical Engineering and Technology
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    • 제3권4호
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    • pp.520-527
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    • 2008
  • This work focuses on the evaluation of active power filter which is controlled by fuzzy logic and neural network based controller for harmonic mitigation and power factor enhancement. The APF consists of a variable DC voltage source and a DC/AC inverter. The task of an APF is to make the line current waveform as close as possible to a sinusoid in phase with the line voltage by injecting the compensation current. The compensation current is estimated using adaptive neural network. Using the estimated current, the proposed APF is controlled using neural network and fuzzy logic. Computer simulations of the proposed APF are performed using MATLAB. The results show that the proposed techniques for the evaluation of APF can reduce the total harmonic distortion less than 3% and improve the power factor of the system to almost unity.

칼만 필터와 퍼지 알고리즘을 이용한 이동 장애물의 위치예측 및 회피에 관한 연구 (Prediction and Avoidance of the Moving Obstacles Using the Kalman Filters and Fuzzy Algorithm)

  • 정원상;최영규;이상혁
    • 대한전기학회논문지:시스템및제어부문D
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    • 제54권5호
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    • pp.307-314
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    • 2005
  • In this paper, we propose a predictive system for the avoidance of the moving obstacle. In the dynamic environment, robots should travel to the target point without collision with the moving obstacle. For this, we need the prediction of the position and velocity of the moving obstacle. So, we use the Kalman filer algorithm for the prediction. And for the application of the Kalman filter algorithm about the real time travel, we obtain the position of the obstacle which has the future time using Fuzzy system. Through the computer simulation studies, we show the effectiveness of the proposed navigational algorithm for autonomous mobile robots.

Visual servoing based on neuro-fuzzy model

  • Jun, Hyo-Byung;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.712-715
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    • 1997
  • In image jacobian based visual servoing, generally, inverse jacobian should be calculated by complicated coordinate transformations. These are required excessive computation and the singularity of the image jacobian should be considered. This paper presents a visual servoing to control the pose of the robotic manipulator for tracking and grasping 3-D moving object whose pose and motion parameters are unknown. Because the object is in motion tracking and grasping must be done on-line and the controller must have continuous learning ability. In order to estimate parameters of a moving object we use the kalman filter. And for tracking and grasping a moving object we use a fuzzy inference based reinforcement learning algorithm of dynamic recurrent neural networks. Computer simulation results are presented to demonstrate the performance of this visual servoing

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색수차 개선을 위한 효율적인 컬러 에지 퍼지 보간 방법 (An efficient Color Edge Fuzzy Interpolation Method for improving a Chromatic Aberration)

  • 변오성
    • 한국컴퓨터정보학회논문지
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    • 제15권10호
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    • pp.59-70
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    • 2010
  • 모바일폰이나 디지털 카메라에서 사용하는 영상 센서의 수광 소자는 한 가지 색만을 기록하는 베이어 패턴이기 때문에 각각의 화소들은 여러 개의컬러 중에서단 하나만의 컬러에 대한 화소값을얻게 된다. 잃어버린화소의 정보는 CFA(Color Filter Array)를 이용하여 그 주위의 화소에 대한 정보를 이용함으로 완전한 컬러 영상을 추론한다. 본 논문은 영상 센서의 수광 소자로부터 획득한 데이터의 평균과 각 컬러 채널 데이터 평균 사이의 관계를 유도하고, 이 관계를 이용하여 색상 보간을 위한 효율적인 에지 컬러 퍼지 보간 방법을 제안하였다. 또한 휘도 신호 채널의 보간은 컬러 노이즈를 감소하고 효율적인 보간을 위해 에지 방향에 따라 퍼지 보간을 하였다. 그리고 본 논문에서 PSNR을 이용하여 제안된 방법이 기존 방법보다 평균 2.4dB 정도 개선됨을 증명하였으며, 시각적으로 원영상의 해상도와 유사한 수준이며, 기존 알고리즘의 영상보다 색수차가 감소된 것을 실험 결과를 통하여 확인하였다.

뉴로-퍼지 기법에 의한 자동차 진단 (Automobile diagnosis by euro-Fuzzy Technique)

  • 신준;오재응
    • 대한기계학회논문집
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    • 제16권10호
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    • pp.1833-1840
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    • 1992
  • 본 연구에서는 자동차의 발달에 따른 정비 전문가의 상대적인 능력 감퇴를 보 완하고 진단의 정확성을 높일 수 있도록 소음계측에 의한 인공 지능적 뉴로-퍼지 진단 기법을 연구하였다. 이를 위하여 진단결과에 영향을 미치는 많은 작용변수와 다양한 차량상태 등을 고려함으로서 보다 신뢰성 있는 결과를 산출해내기 위한 퍼지(fuzzy) 추론 방식의 판단법을 도입하였으며, 진단이 실패했을 경우나 입력된 데이터가 충분하 지 못할 경우에 시스템 자체의 지식을 확장시켜 나갈 수 있도록 해밍네트(hamming net )에 의한 패턴인식 기법을 적용하였다. 그리고 컴퓨터 시뮬레이션과 자동차를 대상 으로 고장진단 실험을 실시하여 기존의 진단기법과의 비교를 통한 뉴로-퍼지 진단기법 의 효율성과 알고리즘의 타당성을 검증하였다.

Type-2 Fuzzy Logic Predictive Control of a Grid Connected Wind Power Systems with Integrated Active Power Filter Capabilities

  • Hamouda, Noureddine;Benalla, Hocine;Hemsas, Kameleddine;Babes, Badreddine;Petzoldt, Jurgen;Ellinger, Thomas;Hamouda, Cherif
    • Journal of Power Electronics
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    • 제17권6호
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    • pp.1587-1599
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    • 2017
  • This paper proposes a real-time implementation of an optimal operation of a double stage grid connected wind power system incorporating an active power filter (APF). The system is used to supply the nonlinear loads with harmonics and reactive power compensation. On the generator side, a new adaptive neuro fuzzy inference system (ANFIS) based maximum power point tracking (MPPT) control is proposed to track the maximum wind power point regardless of wind speed fluctuations. Whereas on the grid side, a modified predictive current control (PCC) algorithm is used to control the APF, and allow to ensure both compensating harmonic currents and injecting the generated power into the grid. Also a type 2 fuzzy logic controller is used to control the DC-link capacitor in order to improve the dynamic response of the APF, and to ensure a well-smoothed DC-Link capacitor voltage. The gained benefits from these proposed control algorithms are the main contribution in this work. The proposed control scheme is implemented on a small-scale wind energy conversion system (WECS) controlled by a dSPACE 1104 card. Experimental results show that the proposed T2FLC maintains the DC-Link capacitor voltage within the limit for injecting the power into the grid. In addition, the PCC of the APF guarantees a flexible settlement of real power exchanges from the WECS to the grid with a high power factor operation.

Occluded Object Motion Estimation System based on Particle Filter with 3D Reconstruction

  • Ko, Kwang-Eun;Park, Jun-Heong;Park, Seung-Min;Kim, Jun-Yeup;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제12권1호
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    • pp.60-65
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    • 2012
  • This paper presents a method for occluded object based motion estimation and tracking system in dynamic image sequences using particle filter with 3D reconstruction. A unique characteristic of this study is its ability to cope with partial occlusion based continuous motion estimation using particle filter inspired from the mirror neuron system in human brain. To update a prior knowledge about the shape or motion of objects, firstly, fundamental 3D reconstruction based occlusion tracing method is applied and object landmarks are determined. And optical flow based motion vector is estimated from the movement of the landmarks. When arbitrary partial occlusions are occurred, the continuous motion of the hidden parts of object can be estimated by particle filter with optical flow. The resistance of the resulting estimation to partial occlusions enables the more accurate detection and handling of more severe occlusions.