Kniha Adaptive Neural Network Based Target Tracking Venkatesh Madyastha

Adaptive Neural Network Based Target Tracking

Adaptive Estimation For Control Of Uncertain Nonlinear Systems With Applications To Target Tracking

Jazyk: Angličtina
Vazba: Brožovaná
Dostupnost: U nakladatele na objednávku
Odesíláme za 17-27 dnů
1 618
Design of nonlinear observers has received §considerable attention since the early development §of m...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2009
Stránek
196
EAN
9783639166941
Enbook ID
06825064
Hmotnost
308
Rozměry
150 x 220 x 12

Kompletní popis

Design of nonlinear observers has received §considerable attention since the early development §of methods for state estimation. The most §popular approach is the extended Kalman filter (EKF) §that goes through significant degradation in the §presence of unmodeled nonlinearities. For uncertain §nonlinear systems, adaptive observers have been §introduced to estimate the unknown parameters where §no apriori information about the unknown parameters §is available. While establishing global results, §these approaches are only applicable to systems §transformable to output feedback form. Over the §recent years, neural network (NN) based §identification and estimation schemes have been §proposed that relax the assumptions on the §system at the price of sacrificing on the global §nature of the results. However, most of the NN based §adaptive observers in the literature require §knowledge of the full dimension of the system, §therefore may not be suitable for systems with §unmodeled dynamics. A novel approach to nonlinear §state estimation, robust to unmodeled dynamics, is §proposed from the perspective of augmenting an EKF §with an NN based adaptive element.

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