Modeling and simulation of power electronic converters
This paper reviews some of the major approaches to modeling and simulation in power
electronics, and provides references that can serve as a starting point for the extensive …
electronics, and provides references that can serve as a starting point for the extensive …
Machine learning and uncertainty quantification for surrogate models of integrated devices with a large number of parameters
This paper deals with the application of the support vector machine (SVM) and the least-
squares SVM regressions to the uncertainty quantification of complex systems with a high …
squares SVM regressions to the uncertainty quantification of complex systems with a high …
An introduction to affine arithmetic
Affine arithmetic (AA) is a model for self-validated computation which, like standard interval
arithmetic (IA), produces guaranteed enclosures for computed quantities, taking into account …
arithmetic (IA), produces guaranteed enclosures for computed quantities, taking into account …
Machine learning for the performance assessment of high-speed links
This paper investigates the application of support vector machine to the modeling of high-
speed interconnects with largely varying and/or highly uncertain design parameters. The …
speed interconnects with largely varying and/or highly uncertain design parameters. The …
An affine arithmetic-based framework for uncertain power flow and optimal power flow studies
This paper proposes a unified framework based on affine arithmetic for computing reliable
enclosures of uncertain power flow (PF) and optimal power flow (OPF) solutions. The main …
enclosures of uncertain power flow (PF) and optimal power flow (OPF) solutions. The main …
Model predictive control of non-isolated DC/DC modular multilevel converter improving the dynamic response
The model predictive control (MPC) is a well-accepted method for controlling power
electronic converters. This paper presents a tailored MPC approach in which the internal …
electronic converters. This paper presents a tailored MPC approach in which the internal …
Multi-objective design and optimization of power electronics converters with uncertainty quantification—Part I: Parametric uncertainty
This article presents a robust multi-objective design and optimization approach with
parametric and model-form uncertainty quantification (MDO with P&MF-UQ). The first part of …
parametric and model-form uncertainty quantification (MDO with P&MF-UQ). The first part of …
Efficient statistical simulation of microwave devices via stochastic testing-based circuit equivalents of nonlinear components
This paper delivers a considerable improvement in the framework of the statistical simulation
of highly nonlinear devices via polynomial chaos-based circuit equivalents. Specifically, a …
of highly nonlinear devices via polynomial chaos-based circuit equivalents. Specifically, a …
Worst-case simulation of discrete linear time-invariant interval dynamic systems
In this paper, a new approach to worst-case simulation of discrete linear time-invariant
interval dynamic systems is proposed. For stable systems, the new approach solves the …
interval dynamic systems is proposed. For stable systems, the new approach solves the …
Surrogate-based worst-case analysis of a knee joint model using Genetic Algorithm
Verification, validation, and uncertainty quantification is generally recognized as a standard
for assessing the credibility of mechanical models. This is especially evident in …
for assessing the credibility of mechanical models. This is especially evident in …