In this paper we study the problem of estimating a given function of a vector of unknowns, called the problem element, by using measurements depending nonlinearly on the problem element and affected by unknown but bounded noise. Assuming that both the solution sought and the measurements depend poly
Recursive membership set estimation for output-error models
โ Scribed by Thierry Clement; Sylviane Gentil
- Publisher
- Elsevier Science
- Year
- 1990
- Tongue
- English
- Weight
- 526 KB
- Volume
- 32
- Category
- Article
- ISSN
- 0378-4754
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โฆ Synopsis
In this paper a new formulation of the problem of identification of discrete time linear models in the case of bounded errors is proposed. The bounds of the error at each sampling time are specified over a measurement noise rather than over an equation error. The method provides parameter uncertainty intervals using an on-line procedure.
๐ SIMILAR VOLUMES
In set membership estimation, conditional problems arise when the estimate must belong to a given set of assigned structure. Conditional projection algorithms provide estimates that are suboptimal in terms of the worst-case estimation error. In order to precisely evaluate the suboptimality level of
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