• Title/Summary/Keyword: Nonlinear estimation

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Iterative parameter estimation for nonlinear measurements (비선형 측정에 대한 반복 계수측정 기법)

  • Chung, Tae-Ho;Je, Chang-Hae;Lyou, Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.314-317
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    • 1993
  • In this paper, the IPE(Iterative Parameter Estimation) methods for the nonlinear measurements are proposed. The IPE methods convert the problems of the parameter estimation for the nonlinear measurements to that of the solution of the nonlinear equations approximately and use several iterative numerical solutions, such as fixed points theory, Newton's methods, quasi-Newton's methods and steepest descent techniques. the IPE methods for the nonlinear measurements-in the case of the error estimation for the inertial navigation systems are simulated, and it is found that the estimation errors for the nonlinear measurements decrease rapidly and converge to almost that of the linear LSE(Least Squares Estimation) when the IPE methods are applied.

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A Study on the Parameter Estimation Algorithm for Nonlinear Systems (비선형 시스템의 계수추정 알고리즘 연구)

  • Lee, Dal-Ho;Seong, Sang-Man
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.7
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    • pp.898-902
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    • 1999
  • In this paper, we proposed an algorithm for estimating parameters of nonlinear continuous-discrete state-space system. This algorithm uses the conventional extended Kalman filter(EKF) for estimating state variables, and modifies the recursive prediction error method for parameter estimation of the nonlinear system. Simulation results for both linear and nonlinear measurements under the environment of process and measurement noises show a convincing performance of the proposed algorithm.

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Nonlinear control of an autonomous mobile robot using nonlinear obserbers

  • Ishikawa, Masato;Sampei, Mitsuji
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.400-404
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    • 1994
  • In this paper, we will investigate the position estimation problem for autonomous mobile robots. Formulating this as a state estimation problem for nonlinear SISO system, then we will apply several types of nonlinear observers. Simulation results of observer-based navigation control will be also provided.

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A Study on Signal Parameters Estimation via Nonlinear Minimization

  • Jeong, Jung-Sik
    • Journal of Navigation and Port Research
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    • v.28 no.4
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    • pp.305-309
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    • 2004
  • The problem for parameters estimation of the received signals impinging on array sensors has long been of great research Interest in a great variety of applications, such as radar, sonar, and land mobile communications systems. Conventional subspace-based algorithms, such as MUSIC and ESPRIT, require an extensive computation of inverse matrix and eigen-decomposition In this paper, we propose a new parameters estimation algorithm via nonlinear minimization, which is simplified computationally and estimates signal parameters simultaneously.

State Estimation and Identification of Nonlinear Systems by Hermitian Expansion of Probability Distributions (Hermite전개법에 의한 비선형계의 상태추정 및 동정에 관한 연구)

  • Kyong Ki Kim
    • 전기의세계
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    • v.22 no.3
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    • pp.49-62
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    • 1973
  • An algorithm for the state estimation and identification of multivariable nonlinear systems with noisy nonlinear observation has been investigated on the basis of the multidimensional Hermitian expansion for the a posteriori probability densities of the predicted observation, the predicted state and the observation conditioned by the state. A new approach for construction of this sequential nonlinear estimator, retaining up to the second order term of the observation error, has been developed, along with the approximation of nonlinear system functions, truncating at the second term. The estimation of the unknown parameters has been established by extending the state estimation technique, regarding the parameters as another state variables. The results of investigation indicate the feasibility of the schemes presented in this paper.

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An Estimation Approach to Robust Adaptive Control of Uncertain Nonlinear Systems with Dynamic Uncertainties

  • Ahn, Choon-Ki;Kim, Beom-Soo;Lim, Myo-Taeg
    • International Journal of Control, Automation, and Systems
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    • v.1 no.1
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    • pp.54-67
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    • 2003
  • In this paper, a novel estimation technique for a robust adaptive control scheme is presented for a class of uncertain nonlinear systems with a general set of uncertainty. For a class of introduced more extended semi-strict feedback forms which generalize the systems studied in recent years, a novel estimation technique is proposed to estimate the states of the fully nonlinear unmodeled dynamics without stringent conditions. With the introduction of powerful functions, the estimation error can be tuned to a desired small region around the origin via the estimator parameters. In addition, with some effective functions, a modified adaptive backstepping for dynamic uncertainties is presented to drive the output to an arbitrarily small region around the origin by an appropriate choice of the design parameters. With our proposed schemes, we can remove or relax the assumptions of the existing results.

Generalized nonlinear percentile regression using asymmetric maximum likelihood estimation

  • Lee, Juhee;Kim, Young Min
    • Communications for Statistical Applications and Methods
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    • v.28 no.6
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    • pp.627-641
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    • 2021
  • An asymmetric least squares estimation method has been employed to estimate linear models for percentile regression. An asymmetric maximum likelihood estimation (AMLE) has been developed for the estimation of Poisson percentile linear models. In this study, we propose generalized nonlinear percentile regression using the AMLE, and the use of the parametric bootstrap method to obtain confidence intervals for the estimates of parameters of interest and smoothing functions of estimates. We consider three conditional distributions of response variables given covariates such as normal, exponential, and Poisson for three mean functions with one linear and two nonlinear models in the simulation studies. The proposed method provides reasonable estimates and confidence interval estimates of parameters, and comparable Monte Carlo asymptotic performance along with the sample size and quantiles. We illustrate applications of the proposed method using real-life data from chemical and radiation epidemiological studies.

Nonlinear hierarchical motion estimation method based on decompositionof the functional domain (범함수 정의역 분할에 바탕을 둔 비선형 계층적 움직임 추정기법)

  • 심동규;박래홍
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.4
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    • pp.807-821
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    • 1996
  • In this paper, we proposed a nonlinear hierarchical mtion estimation method. Generally, the conventional hierarchical motion estimation methods have been proposed for fast convergence and detection of large motions. But they have a common drawback that large error in motion estimation is propapated across motion discontinuities. This artifiact is due to the constriaint of motion continuity and the linear interpolation of motion vectors between hierarchical levels. In this paper, we propose an effective hierarchical motion estimation mechod that is robust to motion discontinuities. The proposed algorithm is based on the decomposition of the functional domain for optimizing the intra-level motion estimation functional. Also, we propose an inter-level nonlinear motion estimation equation rather than using the conventional linearprojection scheme of motion field. computer simulations with several test sequences show tht the proposed algorithm performs better than several conventional methods.

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Nonlinear Control of Torque and Speed of S.I.Engines Using Electric Throttle Control (트로틀 앵글 제어에 의한 내연기관의 토오크 및 속도의 비선형 제어)

  • 원문철;강병배;박문수;김태영
    • Transactions of the Korean Society of Automotive Engineers
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    • v.7 no.6
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    • pp.72-81
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    • 1999
  • A nonlinear engine torque and speed control algorithm using throttle angle control is developed with an engine load torque estimation algorithm. Three 3-dimensional nonlinear engine maps as a part of the nonlinear control algorithm are obtained from steady state engine dynamometer tests. An electric throttle actuator is developed using a stepper motor and a 8 bit micro-processor. The speed control and external load estimation algorithm are tested via engine speed control experiments, and show performance good enough for using various engine torque and speed control applications.

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Real-time Projectile Motion Trajectory Estimation Considering Air Resistance of Obliquely Thrown Object Using Recursive Least Squares Estimation (비스듬히 던진 물체의 공기저항을 고려한 재귀 최소 자승법 기반 실시간 포물선 운동 궤적 추정)

  • Jeong, Sangyoon;Chwa, Dongkyoung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.3
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    • pp.427-432
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    • 2018
  • This paper uses a recursive least squares method to estimate the projectile motion trajectory of an object in real time. The equations of motion of the object are obtained considering the air resistance which occurs in the actual experiment environment. Because these equations consider air resistance, parameter estimation of nonlinear terms is required. However, nonlinear recursive least squares estimation is not suitable for estimating trajectory of projectile in that it requires a lot of computation time. Therefore, parameter estimation for real-time trajectory prediction is performed by recursive least square estimation after using Taylor series expansion to approximate nonlinear terms to polynomials. The proposed method is verified through experiments by using VICON Bonita motion capture system which can get three dimensional coordinates of projectile. The results indicate that proposed method is more accurate than linear Kalman filter method based on the equations of motion of projectile that does not consider air resistance.