Discrete-Time Large-Signal Modeling and Numerical Methods for Flyback Converters

Reiman, Collin; Das, Dhiman; Rosenbaum, Elyse

doi:10.1109/peci.2019.8698921

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…end for 29: end for On the contrary, if an absolute backward error analysis for computing e s −1 A v were considered, see (10), (11), ( 13)- (15), and ( 22) from [25], then…”

Section: Letmentioning

confidence: 99%

“…being A ∈ C n×n and v ∈ C n , and whose solution is in the form Y(t) = e At v ∈ C n -this kind of problem occurs frequently, for example, in control theory-or in applications involving the numerical solutions of fractional partial differential equations [9]. Moreover, the action of the matrix exponential on a vector is also used in physics and engineering fields such as electromagnetics [10], circuit theory [11], acoustic/elastic wave equations [12], seismic wave propagation [13], chemical engineering [14], robotics [15], and so on.…”

Section: Introductionmentioning

confidence: 99%

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Two Taylor Algorithms for Computing the Action of the Matrix Exponential on a Vector

et al. 2022

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The action of the matrix exponential on a vector eAtv, A∈Cn×n, v∈Cn, appears in problems that arise in mathematics, physics, and engineering, such as the solution of systems of linear ordinary differential equations with constant coefficients. Nowadays, several state-of-the-art approximations are available for estimating this type of action. In this work, two Taylor algorithms are proposed for computing eAv, which make use of the scaling and recovering technique based on a backward or forward error analysis. A battery of highly heterogeneous test matrices has been used in the different experiments performed to compare the numerical and computational properties of these algorithms, implemented in the MATLAB language. In general, both of them improve on those already existing in the literature, in terms of accuracy and response time. Moreover, a high-performance computing version that is able to take advantage of the computational power of a GPU platform has been developed, making it possible to tackle high dimension problems at an execution time significantly reduced.

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“…end for 29: end for On the contrary, if an absolute backward error analysis for computing e s −1 A v were considered, see (10), (11), ( 13)- (15), and ( 22) from [25], then…”

Section: Letmentioning

confidence: 99%