Advanced

Recursive estimation of the continuous-time process parameters

de Wit, Carlos Canudas (1986) 25th IEEE Conference on Decision and Control, 1986 In 25th IEEE Conference on Decision and Control, 1986
Abstract
The problem of continuous-time process parameter identification is considered. Filtered input-output process signals are used to create a linear differential equation governed by the same continuous-time process parameters. The estimation scheme is implemented by sampling the filtered signals and using a recursive least squares algorithm (RLS). The choice of filter leads to different parameter convergence properties. Conditions for parameter convergence are established in terms of frequency content of the input signal. The convergence rate is also analysed and an upper bound on the parameter error norm is given. The relation between choice of filter, sampling time selection and quality of the estimates is discussed and exemplified with... (More)
The problem of continuous-time process parameter identification is considered. Filtered input-output process signals are used to create a linear differential equation governed by the same continuous-time process parameters. The estimation scheme is implemented by sampling the filtered signals and using a recursive least squares algorithm (RLS). The choice of filter leads to different parameter convergence properties. Conditions for parameter convergence are established in terms of frequency content of the input signal. The convergence rate is also analysed and an upper bound on the parameter error norm is given. The relation between choice of filter, sampling time selection and quality of the estimates is discussed and exemplified with simulation examples. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Convergence, Differential equations, Frequency, Least squares approximation, Nonlinear filters, Parameter estimation, Recursive Estimation, Resonance light scattering, Signal processing, Signal sampling
in
25th IEEE Conference on Decision and Control, 1986
conference name
25th IEEE Conference on Decision and Control, 1986
external identifiers
  • Scopus:0022956351
DOI
10.1109/CDC.1986.267390
language
English
LU publication?
no
id
04a3d1b5-9d91-43ba-a342-00e500890947 (old id 8517819)
date added to LUP
2016-02-08 10:29:43
date last changed
2016-10-13 04:59:53
@misc{04a3d1b5-9d91-43ba-a342-00e500890947,
  abstract     = {The problem of continuous-time process parameter identification is considered. Filtered input-output process signals are used to create a linear differential equation governed by the same continuous-time process parameters. The estimation scheme is implemented by sampling the filtered signals and using a recursive least squares algorithm (RLS). The choice of filter leads to different parameter convergence properties. Conditions for parameter convergence are established in terms of frequency content of the input signal. The convergence rate is also analysed and an upper bound on the parameter error norm is given. The relation between choice of filter, sampling time selection and quality of the estimates is discussed and exemplified with simulation examples.},
  author       = {de Wit, Carlos Canudas},
  keyword      = {Convergence,Differential equations,Frequency,Least squares approximation,Nonlinear filters,Parameter estimation,Recursive Estimation,Resonance light scattering,Signal processing,Signal sampling},
  language     = {eng},
  series       = {25th IEEE Conference on Decision and Control, 1986 },
  title        = {Recursive estimation of the continuous-time process parameters},
  url          = {http://dx.doi.org/10.1109/CDC.1986.267390},
  year         = {1986},
}