• 제목/요약/키워드: Nonlinear estimator

검색결과 172건 처리시간 0.023초

계산 복잡성이 단순화된 비선형 추정기를 사용한 Bussgang 블라인드 등화 (Bussgang Blind Equalization Using Nonlinear Estimators with Reduced Computational Complexity)

  • 오길남
    • 대한전자공학회논문지SP
    • /
    • 제42권6호
    • /
    • pp.177-186
    • /
    • 2005
  • 이 논문에서는 계산 복잡성이 단순화된 비선형 추정기를 소개하고, 이를 적용한 Bussgang 블라인드 등화 알고리즘을 제안한다. 제안한 알고리즘은 베이즈 추정기가 눈 모형이 닫힌 등화 초기에는 시그모이드 추정기로 잘 근사화되며, 눈 모형이 열린 조건에서는 임계 추정기에 근사화되는 사실을 이용하였다. 제안 방법에서는 매 갱신 마다 채널 왜곡의 정도에 따라 시그모이드 추정기와 임계 추정기를 선택적으로 적용하고, 특히 시그모이드 추정기에 축소 신호점을 도입함으로써 고차 QAM 신호의 블라인드 등화에 적용 시 계산 복잡성을 극히 단순화하는 동시에 블라인드 수렴 특성과 정상상태 성능을 개선할 수 있음을 보인다.

이산 비선형시스템에서의 준최적추정자 (A Suboptimal Estimator Design for Discrete Nonlinear Systems)

  • 이연석;이장규
    • 대한전기학회논문지
    • /
    • 제40권9호
    • /
    • pp.929-936
    • /
    • 1991
  • An estimator for a discrete nonlinear system is derived in the sense of minimum mean square error. An optimal estimator for nonlinear system is very difficult to find and it will be infinite dimensional even if it is found. It has been known that the statistical linearization technique makes it possible to obtain a finite dimensional estimator. In this paper, the procedure of its derivation using the statistical linearization technique that gives an exact mean and variance information is introduced in the sense of minimum mean square error. The derived estimator cannot be clainmed to be globally optimal estimator because it uses the Gaussian assumption to the non-Gaussian distributed nonlinear output. However, the proposed filter exhibits a better performance compared to extended Kalman filter. Simulation results of a simple example present the improvement of the proposed filter in convergent property over the extended Kalman filter.

  • PDF

Parameter Estimation in a Complex Non-Stationary and Nonlinear Diffusion Process

  • So, Beong-Soo
    • Journal of the Korean Statistical Society
    • /
    • 제29권4호
    • /
    • pp.489-499
    • /
    • 2000
  • We propose a new instrumental variable estimator of the complex parameter of a class of univariate complex-valued diffusion processes defined by the possibly non-stationary and/or nonlinear stochastic differential equations. On the basis of the exact finite sample distribution of the pivotal quantity, we construct the exact confidence intervals and the exact tests for the parameter. Monte-Carlo simulation suggests that the new estimator seems to provide a viable alternative to the maximum likelihood estimator (MLE) for nonlinear and/or non-stationary processes.

  • PDF

Nonlinear Regression Quantile Estimators

  • Park, Seung-Hoe;Kim, Hae kyung;Park, Kyung-Ok
    • Journal of the Korean Statistical Society
    • /
    • 제30권4호
    • /
    • pp.551-561
    • /
    • 2001
  • This paper deals with the asymptotic properties for statistical inferences of the parameters in nonlinear regression models. As an optimal criterion for robust estimators of the regression parameters, the regression quantile method is proposed. This paper defines the regression quintile estimators in the nonlinear models and provides simple and practical sufficient conditions for the asymptotic normality of the proposed estimators when the parameter space is compact. The efficiency of the proposed estimator is especially well compared with least squares estimator, least absolute deviation estimator under asymmetric error distribution.

  • PDF

Estimation of the Polynomial Errors-in-variables Model with Decreasing Error Variances

  • Moon, Myung-Sang;R. F. Gunst
    • Journal of the Korean Statistical Society
    • /
    • 제23권1호
    • /
    • pp.115-134
    • /
    • 1994
  • Polynomial errors-in-variables model with one predictor variable and one response variable is defined and an estimator of model is derived following the Booth's linear model estimation procedure. Since polynomial model is nonlinear function of the unknown regression coefficients and error-free predictors, it is nonlinear model in errors-in-variables model. As a result of applying linear model estimation method to nonlinear model, some additional assumptions are necessary. Hence, an estimator is derived under the assumption that the error variances are decrasing as sample size increases. Asymptotic propoerties of the derived estimator are provided. A simulation study is presented to compare the small sample properties of the derived estimator with those of OLS estimator.

  • PDF

Nonlinear model predictive control of chemical reactors

  • Lee, Jongku;Park, Sunwon
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
    • /
    • pp.419-424
    • /
    • 1992
  • A robust nonlinear predictive control strategy using a disturbance estimator is presented. The disturbance estimator is comprised of two parts: one is the disturbance model parameter adaptation and the other is future disturbance prediction. RLSM(recurrsive least square method) with a forgetting factor is used to de the uncertain distance model parameters and for the future disturbance prediction, future process outputs and inputs projected by the process model are used. The simulation results for chemical reactors indicate that a substantial improvement in nonlinear predictive control performance is possible using the disturbance estimator.

  • PDF

스튜어트 플랫폼의 견실한 순기구학 추정기 설계 (Robust estimator design for the forward kinematics solution of stewart platform)

  • 강지윤;김동환;이교일
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
    • /
    • pp.28-31
    • /
    • 1996
  • We propose an estimator design method of Stewart platform, which gives the 6DOF, positions and velcities of Stewart platform from the measured cylinder length. The solution of forward kinematics is not solved yet as a useful realtime application tool because of the complexity of the equation with multiple solutions. Hence we suggest an nonlinear estimator for the forward kinematics solution using Luenberger observer with nonlinear error correction term. But the way of residual gain selection of the estimator is not clear, so we suggest an algebraic Riccati equation for gain matrix using Lyapunov method. This algorithm gives the sufficient condition of the stability of error dynamics and can be extended to general nonlinear system.

  • PDF

고기동 BTT미사일을 위한 효과적인 시선변화율 추정 방법 (An Efficient Estimation Method of Line-of-Sight Rate in High Maneuvering BTT Missiles)

  • 송은한;권정훈;하인중
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
    • /
    • pp.201-203
    • /
    • 2006
  • This paper describes a new LOS(Line-of-Sight) estimator for BTT missiles. The dynamic models of LOS rate and a seeker are derived. Based on these dynamic models, we design a nonlinear estimator, which takes into account roll motion of BTT missiles and sensor noises. Simulation results show that the LOS rate estimates of the proposed estimator are more accurate than those of the conventional estimator.

  • PDF

퍼지신경망과 강인한 마찰 상태 관측기를 이용한 비선형 마찰 서보시스템에 대한 강인 제어 (Robust Control for Nonlinear Friction Servo System Using Fuzzy Neural Network and Robust Friction State Observer)

  • 한성익
    • 한국정밀공학회지
    • /
    • 제25권12호
    • /
    • pp.89-99
    • /
    • 2008
  • In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

강인한 마찰 상태 관측기와 순환형 퍼지신경망 관측기를 이용한 비선형 마찰제어 (Nonlinear Friction Control Using the Robust Friction State Observer and Recurrent Fuzzy Neural Network Estimator)

  • 한성익
    • 한국공작기계학회논문집
    • /
    • 제18권1호
    • /
    • pp.90-102
    • /
    • 2009
  • In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.