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Alfredo Germani
Researcher at University of L'Aquila
Publications - 228
Citations - 4086
Alfredo Germani is an academic researcher from University of L'Aquila. The author has contributed to research in topics: Nonlinear system & Linear system. The author has an hindex of 28, co-authored 225 publications receiving 3589 citations. Previous affiliations of Alfredo Germani include University of Calabria & Università Campus Bio-Medico.
Papers
More filters
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A Luenberger-like observer for nonlinear systems
TL;DR: In this paper, a state observer is proposed for nonlinear continuous time systems which extends the well known Luenberger observer, and on the basis of simple assumptions on the regularity of the system equations, which are generally satisfied for physically meaningful dynamic systems, the global asymptotic convergence of the estimated state towards the true state is shown.
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A new approach to state observation of nonlinear systems with delayed output
TL;DR: A new approach is presented for the construction of a state observer for nonlinear systems when the output measurements are available for computations after a nonnegligible time delay using a chain of observation algorithms reconstructing the system state at different delayed time instants.
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Polynomial Filtering for Linear Discrete Time Non-Gaussian Systems
TL;DR: A new filtering approach for linear discrete time non-Gaussian systems that generalizes a previous result concerning quadratic filtering and will be the mean square optimal one among those estimators that take into account $
u$-polynomials of the last $\Delta$ observations.
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Polynomial filtering of discrete-time stochastic linear systems with multiplicative state noise
TL;DR: The problem of finding an optimal polynomial state estimate for the class of stochastic linear models with a multiplicative state noise term is studied and a technique of state augmentation is used, leading to the definition of a general Polynomial filter.
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An observer for a class of nonlinear systems with time varying observation delay
TL;DR: The technique used to prove the asymptotical convergence to zero of the observation error, based on the Lyapunov–Razumikhin approach, does not require any assumption about the dependence of the delay on the time.