Tesi etd-03022009-140645 |
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Tipo di tesi
Tesi di dottorato di ricerca
Autore
CRISOSTOMI, EMANUELE
URN
etd-03022009-140645
Titolo
A particle approach to the analysis and estimation of nonlinear dynamical systems
Settore scientifico disciplinare
ING-INF/04
Corso di studi
AUTOMATICA, ROBOTICA E BIOINGEGNERIA
Relatori
Relatore Prof. Caiti, Andrea
Parole chiave
- Nonlinear systems
- particle filters
- set-membership
Data inizio appello
21/04/2009
Consultabilità
Non consultabile
Data di rilascio
21/04/2049
Riassunto
The PhD thesis deals with the general model based estimation problem, which is solved here using particle filters as basic tool. Particle filters are sequential Monte Carlo methods able to solve the nonlinear filtering problem with the appealing feature of dropping otherwise mandatory assumptions of linear models and/or Gaussian distributions. The main contribution of this PhD thesis is to develop new algorithms where particle filters are used within a set-membership framework. Thanks to the combined approach, it is possible to estimate the probability distribution of the unknown real state and at the same time keeping a bound on the maximum error that can be committed.
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