Robust On-Line Estimation
(1999) In MSc ThesesDepartment of Automatic Control
- Abstract
- In the presence if poor excitation and abrupt changes of a time-varying system the Recursive least square (RLS) with forgetting factor is not able to track the parameters in a suitable way. The purpose of this thesis is to investigate different kinds of proposals of algorithms to deal with the phenomenons arising, such as estimator windup or too slow convergence of the estimations. Attention is also paid to prior information of the bounds of the system and two variants of RLS are presented to prevent the estimation to exceed these bounds. All algorithms are introduced theoretically and their performances are verified via simulation studies. <br><br> Finally the application of the algorithms is illustrated. Incorporating four of our... (More)
- In the presence if poor excitation and abrupt changes of a time-varying system the Recursive least square (RLS) with forgetting factor is not able to track the parameters in a suitable way. The purpose of this thesis is to investigate different kinds of proposals of algorithms to deal with the phenomenons arising, such as estimator windup or too slow convergence of the estimations. Attention is also paid to prior information of the bounds of the system and two variants of RLS are presented to prevent the estimation to exceed these bounds. All algorithms are introduced theoretically and their performances are verified via simulation studies. <br><br> Finally the application of the algorithms is illustrated. Incorporating four of our algorithms in the RLD we succeed in estimating the mass of a car and the slope of a road on-line by simulating a mathematical model. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8848504
- author
- Gustafsson, Lars and Olsson, Mikael
- supervisor
- organization
- year
- 1999
- type
- H3 - Professional qualifications (4 Years - )
- subject
- publication/series
- MSc Theses
- report number
- TFRT-5633
- ISSN
- 0280-5316
- language
- English
- id
- 8848504
- date added to LUP
- 2016-03-24 11:15:56
- date last changed
- 2016-03-24 11:15:56
@misc{8848504, abstract = {{In the presence if poor excitation and abrupt changes of a time-varying system the Recursive least square (RLS) with forgetting factor is not able to track the parameters in a suitable way. The purpose of this thesis is to investigate different kinds of proposals of algorithms to deal with the phenomenons arising, such as estimator windup or too slow convergence of the estimations. Attention is also paid to prior information of the bounds of the system and two variants of RLS are presented to prevent the estimation to exceed these bounds. All algorithms are introduced theoretically and their performances are verified via simulation studies. <br><br> Finally the application of the algorithms is illustrated. Incorporating four of our algorithms in the RLD we succeed in estimating the mass of a car and the slope of a road on-line by simulating a mathematical model.}}, author = {{Gustafsson, Lars and Olsson, Mikael}}, issn = {{0280-5316}}, language = {{eng}}, note = {{Student Paper}}, series = {{MSc Theses}}, title = {{Robust On-Line Estimation}}, year = {{1999}}, }