Time-varying parameter estimation under stochastic perturbations using LSM

نویسنده

  • Jesica Escobar
چکیده

In this paper, we deal with the problem of continuous-time time-varying parameter estimation in stochastic systems, under three different kinds of stochastic perturbations: additive and multiplicative white noise, and coloured noise. The proposed algorithm is based on the least squares method with forgetting factor. Some numerical examples illustrate the effectiveness of the proposed algorithm. An analysis of the estimation error for the system under the three different kinds of perturbations is presented.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Time-Varying Parameter Estimation under Stochastic Perturbations Using LSM, Report no. LiTH-ISY-R-3019

In this paper, we deal with the problem of continuous-time timevarying parameter estimation in stochastic systems, under 3 different kinds of stochastic perturbations: additive and multiplicative white noise, and colored noise. The proposed algorithm is based on the Least Squares Method with forgetting factor. Some numerical examples illustrate the effectiveness of the proposed algorithm. An an...

متن کامل

Robust Continuous-Time Matrix Estimation under Dependent Noise Perturbations: Sliding Modes Filtering and LSM with Forgetting

This paper deals with time-varying parameter estimation of stochastic systems under dependent noise perturbations. The filter, which generates this dependent noise from a standard “white noise,” is assumed to be partially known (a nominal plant plus a bounded deviation). The considered approach consists of two consecutive steps. At the first step, the application of a sliding-mode-type algorith...

متن کامل

Robust stability of stochastic fuzzy impulsive recurrent neural networks with\ time-varying delays

In this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the Takagi-Sugeno (T-S) fuzzy models is considered. A novel Linear Matrix Inequality (LMI)-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

متن کامل

Online Monitoring for Industrial Processes Quality Control Using Time Varying Parameter Model

A novel data-driven soft sensor is designed for online product quality prediction and control performance modification in industrial units. A combined approach of time variable parameter (TVP) model, dynamic auto regressive exogenous variable (DARX) algorithm, nonlinear correlation analysis and criterion-based elimination method is introduced in this work. The soft sensor performance validation...

متن کامل

The impact of model and rainfall forcing errors on characterizing soil moisture uncertainty in land surface modeling

The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from sa...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • IMA J. Math. Control & Information

دوره 29  شماره 

صفحات  -

تاریخ انتشار 2012