• Title/Summary/Keyword: Nonlinear estimation

Search Result 1,174, Processing Time 0.037 seconds

Batch Time Interval and Initial State Estimation using GMM-TS for Target Motion Analysis (GMM-TS를 이용한 표적기동분석용 배치구간 및 초기상태 추정 기법)

  • Kim, Woo-Chan;Song, Taek-Lyul
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.18 no.3
    • /
    • pp.285-294
    • /
    • 2012
  • Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

Experimental Study of Spacecraft Pose Estimation Algorithm Using Vision-based Sensor

  • Hyun, Jeonghoon;Eun, Youngho;Park, Sang-Young
    • Journal of Astronomy and Space Sciences
    • /
    • v.35 no.4
    • /
    • pp.263-277
    • /
    • 2018
  • This paper presents a vision-based relative pose estimation algorithm and its validation through both numerical and hardware experiments. The algorithm and the hardware system were simultaneously designed considering actual experimental conditions. Two estimation techniques were utilized to estimate relative pose; one was a nonlinear least square method for initial estimation, and the other was an extended Kalman Filter for subsequent on-line estimation. A measurement model of the vision sensor and equations of motion including nonlinear perturbations were utilized in the estimation process. Numerical simulations were performed and analyzed for both the autonomous docking and formation flying scenarios. A configuration of LED-based beacons was designed to avoid measurement singularity, and its structural information was implemented in the estimation algorithm. The proposed algorithm was verified again in the experimental environment by using the Autonomous Spacecraft Test Environment for Rendezvous In proXimity (ASTERIX) facility. Additionally, a laser distance meter was added to the estimation algorithm to improve the relative position estimation accuracy. Throughout this study, the performance required for autonomous docking could be presented by confirming the change in estimation accuracy with respect to the level of measurement error. In addition, hardware experiments confirmed the effectiveness of the suggested algorithm and its applicability to actual tasks in the real world.

Observer for Nonlinear Systems Using Approximate Observer Form (근사 관측기 형태를 이용한 비선형 시스템의 관측기)

  • 이성렬;신현석;박민용
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 2000.10a
    • /
    • pp.207-207
    • /
    • 2000
  • This paper presents an observer for nonlinear systems using approximate observer form. It is shown that if a nonlinear system is approximately error linearizable, then there exists a local nonlinear observer whose estimation error converges exponentially to zero. Since the proposed method relaxes strong geometric conditions of previous works, it improves the existing results for a nonlinear observer design. Finally, some examples are given to show the effectiveness of this scheme.

  • PDF

A Nonlinear Observer for the Estimation of the Full State of a Sawyer Motor (평판 모터 상태 관측을 위한 비선형 관측기)

  • Kim, Won-Hee;Chung, Chung-Choo
    • The Transactions of The Korean Institute of Electrical Engineers
    • /
    • v.59 no.12
    • /
    • pp.2292-2297
    • /
    • 2010
  • To improve the performances of Sawyer motors and to regulate yaw rotation, various feedback control methods have been developed. Almost all of these methods require information on the position, velocity or full state of the motor. Therefore, in this paper, a nonlinear observer is designed to estimate the full state of the four forcers in a Sawyer motor. The proposed method estimates the full state using only positional feedback. Generally, Sawyer motors are operated within a yaw magnitude of several degrees; outside of this range, Sawyer motors step out. Therefore, this observer design assumes that the yaw is within ${\pm}90^\b{o}$. The convergence of the estimation error is proven using the Lyapunov method. The proposed observer guarantees that the estimation error globally exponentially converges to zero for all arbitrary initial conditions. Furthermore, since the proposed observer does not require any transformation, it may result in a reduction in the commutation delay. The simulation results show the performance of the proposed observer.

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

  • Moon, Myung-Sang;R. F. Gunst
    • Journal of the Korean Statistical Society
    • /
    • v.23 no.1
    • /
    • 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

A Note on State Estimation Problems for Perspective Linear Systems Corrupted by Noises

  • Kondo, Ryota;Abdursul, Rixat;Inaba, Hiroshi
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 2005.06a
    • /
    • pp.480-485
    • /
    • 2005
  • Perspective dynamical systems arise in machine vision problems, in which only perspective observation is available. This paper considers the state estimation problem for a rigid body moving in three dimensional spaces using the image data obtained by a CCD camera or some other means. Because the motion of the rigid body and the observed data are generally corrupted by noises, it is necessary to seek a state estimation method to reduce the influence of the noises. In this paper, by means of computer simulations for a simple example, we examine the sensitivity to the noises of the nonlinear observer developed in the recent paper ([1] R. Abdursul, H. Inaba and B. Ghosh, Nonlinear observers for perspective time-invariant linear systems, Automatica, vol. 40, Issue 3, pp. 481-490, 2004) and the effectiveness of the Extended Kalman Filter.

  • PDF

A PARAMETER ESTIMATION METHOD FOR MODEL ANALYSIS

  • Oh Se-Young;Kwon Sun-Joo;Yun Jae-Heon
    • Journal of applied mathematics & informatics
    • /
    • v.22 no.1_2
    • /
    • pp.373-385
    • /
    • 2006
  • To solve a class of nonlinear parameter estimation problems, a method combining the regularized structured nonlinear total least norm (RSNTLN) method and parameter separation scheme is suggested. The method guarantees the convergence of parameters and has an advantages in reducing the residual norm over the use of RSNTLN only. Numerical experiments for two models appeared in signal processing show that the suggested method is more effective in obtaining solution and parameter with minimum residual norm.

States Estimation of Nonlinear Stochastic System Using Single Term Walsh Series (월쉬 단일항 전개를 이용한 비선형 확률 시스템의 상태추정)

  • Lim, Yun-Sik
    • The Transactions of the Korean Institute of Electrical Engineers P
    • /
    • v.57 no.2
    • /
    • pp.115-120
    • /
    • 2008
  • The EKF(Extended Kalman filter) method which is the state estimation algorithm of nonlinear stochastic system depends on the initial error and the estimated states. Therefore, the divergence of the estimated state can be caused if the initial values of the estimated states are not chosen as approximate real state values. In this paper, the demerit of the existing EKF method is improved using the EKF algorithm transformated by STWS(Single Term Walsh Series). This method linearizes each sampling interval of continous-time system through the derivation of an algebraic iterative equation without discretizing continuous system by the characteristic of STWS, the convergence of the estimated states can be improved. The validity of the proposed method is checked through comparison with the existing EKF method in simulation.

Sensorless Control of Permanent Magnet Synchronous Motors with Compensation for Parameter Uncertainty

  • Yang, Jiaqiang;Mao, Yongle;Chen, Yangsheng
    • Journal of Electrical Engineering and Technology
    • /
    • v.12 no.3
    • /
    • pp.1166-1176
    • /
    • 2017
  • Estimation errors of the rotor speed and position in sensorless control systems of Permanent Magnet Synchronous Motors (PMSM) will lead to low efficiency and dynamic-performance degradation. In this paper, a parallel-type extended nonlinear observer incorporating the nominal parameters is constructed in the stator-fixed reference frame, with rotor position, speed, and the load torque simultaneously estimated. The stability of the extended nonlinear observer is analyzed using the indirect Lyapunov's method, and observer gains are selected according to the transfer functions of the speed and position estimators. Taking into account the parameter inaccuracies issue, explicit estimation error equations are derived based on the error dynamics of the closed-loop sensorless control system. An equivalent flux error is defined to represent the back Electromotive Force (EMF) error caused by the inaccurate motor parameters, and a compensation strategy is designed to suppress the estimation errors. The effectiveness of the proposed method has been validated through simulation and experimental results.

Iterative Polynomial Fitting Technique Using Polynomial Coefficients for the Nonlinear Line Array Shape Estimation (비선형 선배열 형상 추정을 위한 계수 반복 다항 근사화 기법)

  • Cho, Chom Gun
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.9 no.2 s.25
    • /
    • pp.20-25
    • /
    • 2006
  • Low frequency towed line array with high array gain and beam resolution is a long range surveillance sensor for anti-submarine warfare. The beam characteristics is however deteriorated due to the distorted line array sensor caused by low towing speed, wind, current, and towing ship maneuvering. An adaptive beamforming method is utilized in this paper to enhance the distorted line array beam performance by estimating and compensating the nonlinear array shape. A polynomial curve fitting in the least square sense is used to estimate the array shape iteratively with the distributed heading sensors data along the array. Real time array shape estimation and nonlinear array beam calculation is applied to a very long towed line array sensor system and the beam performance is evaluated and compared to the linear beamformer for the simulation and sea trial data.