• Title/Summary/Keyword: Fuzzy Estimator

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Fuzzy Estimator for Gain Scheduling and its Application to Magnetic Suspension

  • Lee, S.H.;J.T. Lim
    • 제어로봇시스템학회:학술대회논문집
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    • pp.382-382
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    • 2000
  • The external force disturbance is the one of the main causes that deteriorate the performance of the magnetic suspension. Thus, this paper develops a fuzzy estimator for gain scheduling control of magnetic suspension systems suffering from the unknown disturbance. The proposed fuzzy estimator computes the disturbance injected to the plant and the gain scheduled controller generates the corresponding stabilizing control input associated with the estimated disturbance. In the simulation results we confirm the novelty of the proposed control scheme comparing with the other method using a feedback linearization.

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Fuzzy Estimator for Gain Scheduling and its Appliation to Magnetic Suspension

  • Lee, Seon-Ho;Lim, Jong-Tae
    • Transactions on Control, Automation and Systems Engineering
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    • v.3 no.2
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    • pp.106-110
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    • 2001
  • The external force disturbance is the one of the main causes that deteriorate the performance of the magnetic suspension. Thus, this paper develops a fuzzy estimator for gain scheduling control of magnetic suspension system suffering from the unknown disturbance. The propose fuzzy estimator computes the disturbance injected to the plant the gain scheduled controller generates the corresponding stabilizing control input associated with estimated disturbance. In the simulation results we confirm the novelty of the proposed control scheme comparing with the other method using a feedback linearization.

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Fuzzy estimation of minor flank wear in face milling (면삭밀링가공시 공구 부절삭날 마모길이의 퍼지적 평가)

  • T.J. Ko;D.W. Cho
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.4
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    • pp.28-38
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    • 1995
  • The flank wear at the minor cutting edge significantly affects the geometric accuracy and surface roughness in finish machining. A fuzzy estimator based on a fuzzy inference algorithm with a max-min composition rule is introduced to evaluate the minor flank wear length. The features sensitive to minor flank wear are extracted from the dispersion analysis of a time series AR model of the feed directional acceleration signal. These features, dispersions, are used for constructing linguistic rules, and then the fuzzy inferences are carried out with test data sets collected under various cutting conditions. The proposed system turns out to be effective for estimating minor flank wear length.

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A Study on the State Estimaion of Dynamic system using Fuzzy Estimator (퍼지 추정기에의한 동적 시스템의 상태 추정에 관한 연구)

  • 문주영;박승현;이상배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.350-355
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    • 1997
  • The problem of mathematical model for an unknown system by measureing its input-output data pairs is generally referred to as state estimates. The state estimation problem is often of importance in its own right since we may want to know the value of the states. For instance, in navigation, we may take noisy positional fixes using satelite or radar navigation, and the estimator can use these measurements to provide accurate estimates of current position, hedaing, and velocity. And the state estimates can also be used for control purposes. Then it is very important to know the state of plant. In this paper, the theory of the minimization of a loss function was used to design the fuzzy system. Here, the used teory is Least Square Esimation method. This parametrization has the Linear in the parameters charcteristic that allows standard parameter estimation technique to be used to estimate the parameters of the fuzzy system. The combination of the fuzzy system and the estimation m thod then performs as a nonlinear estimator. If several fuzzy label are defined for the input variables at the antecedent part, the fuzzy system then behaves as a collection of nonlinear estimators where different regions of rules have different parameters. In simulation results, the fuzzy model controlled a difference in the structure between the actual plant and the fuzzy estimator. It is also proved that the fuzzy system is equivalent to its transformed system. therefore we was able to get the state space equation of system with the estimated paramater.

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Development of Fuzzy Travel Time Estimator for Interrupted Traffic Flow (단속류 퍼지 통행시간 추정기의 개발)

  • 오기도;김영찬
    • Journal of Korean Society of Transportation
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    • v.18 no.5
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    • pp.57-67
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    • 2000
  • Two fuzzy travel time estimators for interrupted traffic flow were developed based on field survey data and simulation data 7hat is collected from DETSIM, which is microscopic traffic simulation model that car-following theory is applied. One is FETTOS(Fuzzy Estimator of Travel Time using Occupancy and Spot speed) and the other is FETTOS(Fuzzy Estimator of Travel Speed using Volume and Occupancy). Fuzzy logic controller was applied to the estimators to deal with non-linear relationship between traffic variables and travel time. According to results of simulation and field survey. estimation of travel time can be modeled by using percent occupancy better than any other traffic variables. Detector location from storyline and signal timing Plan of intersection are affected to estimate travel time. With a few findings, the estimator was constructed and its performance was tested for observed travel time data and simulated data. FETTOS which needs signal timing plan and detector location estimates travel time with accurate better than FETSVO does. However. FETSVO has excellent transferability because the estimator needs set of input data only; volume and time mean speed.

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Estimation of structure system input force using the inverse fuzzy estimator

  • Lee, Ming-Hui
    • Structural Engineering and Mechanics
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    • v.37 no.4
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    • pp.351-365
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    • 2011
  • This study proposes an inverse estimation method for the input forces of a fixed beam structural system. The estimator includes the fuzzy Kalman Filter (FKF) technology and the fuzzy weighted recursive least square method (FWRLSM). In the estimation method, the effective estimator are accelerated and weighted by the fuzzy accelerating and weighting factors proposed based on the fuzzy logic inference system. By directly synthesizing the robust filter technology with the estimator, this study presents an efficient robust forgetting zone, which is capable of providing a reasonable trade-off between the tracking capability and the flexibility against noises. The period input of the fixed beam structure system can be effectively estimated by using this method to promote the reliability of the dynamic performance analysis. The simulation results are compared by alternating between the constant and adaptive and fuzzy weighting factors. The results demonstrate that the application of the presented method to the fixed beam structure system is successful.

Vision-Based Obstacle Collision Risk Estimation of an Unmanned Surface Vehicle (무인선의 비전기반 장애물 충돌 위험도 평가)

  • Woo, Joohyun;Kim, Nakwan
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.12
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    • pp.1089-1099
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    • 2015
  • This paper proposes vision-based collision risk estimation method for an unmanned surface vehicle. A robust image-processing algorithm is suggested to detect target obstacles from the vision sensor. Vision-based Target Motion Analysis (TMA) was performed to transform visual information to target motion information. In vision-based TMA, a camera model and optical flow are adopted. Collision risk was calculated by using a fuzzy estimator that uses target motion information and vision information as input variables. To validate the suggested collision risk estimation method, an unmanned surface vehicle experiment was performed.

리튬 2차 전지의 1차원 열적 특성을 고려한 지능형 용량예측

  • Lee, Jeong-Su;Ho, Bin;Kim, Gwang-Seon;Im, Geun-Uk;Jo, Jang-Gun;Jo, Hyeon-Chan
    • Proceedings of the Korean Society Of Semiconductor Equipment Technology
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    • pp.244-249
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    • 2007
  • In this paper, in order to get the characteristics of the lithium secondary cell, such as cycle life, charge and discharge characteristic, temperature characteristic, self-discharge characteristic and the capacity recovery rate etc, we build a mathematical model of battery. In this one-dimensional model, Seven governing equations are made to solve seven variables $c,\;c_s,\;{\Phi}_1,\;{\Phi}_2,\;i_2,\;j\;and\;T$. The mathematical model parameters used in this model have been adjusted according to the experimental data measured in our lab. The connecting research of this study is to get an accurate estimate of the capacity of battery through comparison of results from simulation and fuzzy logic system. So the result data from this study is reorganized to fit the fuzzy logic algorithm.

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Nonlinear structural system wind load input estimation using the extended inverse method

  • Lee, Ming-Hui
    • Wind and Structures
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    • v.17 no.4
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    • pp.451-464
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    • 2013
  • This study develops an extended inverse input estimation algorithm with intelligent adaptive fuzzy weighting to effectively estimate the unknown input wind load of nonlinear structural systems. This algorithm combines the extended Kalman filter and recursive least squares estimator with intelligent adaptive fuzzy weighting. This study investigated the unknown input wind load applied on a tower structural system. Nonlinear characteristics will exist in various structural systems. The nonlinear characteristics are particularly more obvious when applying larger input wind load. Numerical simulation cases involving different input wind load types are studied in this paper. The simulation results verify the nonlinear characteristics of the structural system. This algorithm is effective in estimating unknown input wind loads.