Giordano Scarciotti

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Model reduction by moment matching for “interpolation signals” which do not have an implicit model, i.e. they do not satisfy a differential equation, is considered. Particular attention is devoted to discontinuous, possibly periodic, signals. The notion of moment is reformulated using an integral matrix equation. It is shown that, under specific conditions,(More)
Abstract: The model reduction problem by moment matching for linear time-delay systems is addressed. A parameterized family of models achieving moment matching is characterized. The parameters can be exploited to derive a delay-free reduced order model or reduced order models with additional properties. The theory is illustrated by an example borrowed from(More)
An algorithm for the estimation of the moments of linear single-input, single-output (SISO) systems and linear time-delay SISO systems from input/output data is proposed. It is proved that the estimate converges to the moments of the system. The estimate is exploited to construct a family of reduced order models. These models asymptotically match the(More)
The finite-horizon optimal control problem with input constraints consists in controlling the state of a dynamical system over a finite time interval (possibly unknown) minimizing a cost functional, while satisfying hard constraints on the input. For linear systems the solution of the problem often relies upon the use of bang-bang control signals. For(More)
The model reduction problem for (single-input, single-output) linear and nonlinear systems is addressed using the notion of moment. A re-visitation of the linear theory allows to obtain novel results for linear systems and to develop a nonlinear enhancement of the notion of moment. This, in turn, is used to pose and solve the model reduction problem by(More)