Recursive estimation of the continuous-time process parameters
(1986) 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:
https://lup.lub.lu.se/record/8517819
- author
- de Wit, Carlos Canudas
- organization
- publishing date
- 1986
- 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
- host publication
- 25th IEEE Conference on Decision and Control, 1986
- conference name
- 25th IEEE Conference on Decision and Control, 1986
- conference location
- Athens, Greece
- conference dates
- 1986-12-10 - 1986-12-12
- 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
- 2016-04-04 14:05:55
- date last changed
- 2021-09-19 04:44:47
@inproceedings{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}}, booktitle = {{25th IEEE Conference on Decision and Control, 1986}}, keywords = {{Convergence; Differential equations; Frequency; Least squares approximation; Nonlinear filters; Parameter estimation; Recursive Estimation; Resonance light scattering; Signal processing; Signal sampling}}, language = {{eng}}, title = {{Recursive estimation of the continuous-time process parameters}}, url = {{http://dx.doi.org/10.1109/CDC.1986.267390}}, doi = {{10.1109/CDC.1986.267390}}, year = {{1986}}, }