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From a sparse set of large-scale linear time-invariant dynamical models, a methodology to generate a low-order parameter-dependent and uncertain model, with guaranteed bounds on the approximation error, is first obtained using advanced approximation and interpolation techniques. Second, the stability of the aforementioned model, represented as a linear fractional representation and subject to actuator...
In this paper, the problem of determining the approximate stability regions of large-scale time-delay systems (LS TDS) is solved using model approximation techniques. To achieve this, an ℋ2-oriented approximation algorithm, referred to as TF-IRKA [1], is considered. This algorithm has been shown to be well suited for the approximation of infinite-dimensional systems into finite-dimensional ones. We...
A methodology to generate a parameter dependent uncertain large-scale aeroservoelastic aircraft model, with guaranteed bounds on the approximation error is firstly obtained using adavanced approximation and interpolation techniques. Secondly, the global stability of the aforementionned uncertain parameter dependent aircraft model, represented as a Linear Fractional Representation (LFR), subject to...
In this paper, a new Iterative Eigenvector Tangential Interpolation Algorithm (IETIA) is proposed to approximate large-scale LTI models, allowing to achieve ℌ2 optimality-like conditions while preserving some user-defined eigenvalues. The proposed algorithm is also shown to be applicable to a certain class of LPV models. Numerical applications on standard model reduction benchmarks assess the effectiveness...
In many highly technological engineering fields, the use of dedicated computer-based dynamical system modeling software often leads to large dimensional Linear Time Invariant (LTI) models. These kind of models, composed of a large amount of variables might render drastically inefficient many analysis, control design and optimization techniques. As a matter of fact, considerable attention has been...
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