The problem of estimating the largest possible component of the state of a parameter dependent linear system in presence of unknown inputs is considered. Using a geometric approach and suitable defined invariant subspaces, that capture the concept of robustness with respect to parameter variation, a procedure for detecting the largest component of the state that may possibly be estimated together with a construction of the observer system and a technique for analyzing its asymptotic behavior is provided.
Titolo: | Unknown Inputs, Robust State Observation for Linear Parameter Varying Systems |
Autori: | |
Data di pubblicazione: | 2007 |
Abstract: | The problem of estimating the largest possible component of the state of a parameter dependent linear system in presence of unknown inputs is considered. Using a geometric approach and suitable defined invariant subspaces, that capture the concept of robustness with respect to parameter variation, a procedure for detecting the largest component of the state that may possibly be estimated together with a construction of the observer system and a technique for analyzing its asymptotic behavior is provided. |
Handle: | http://hdl.handle.net/11566/44518 |
ISBN: | 978-395241738-6 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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