Concept

Scenario optimization

Related publications (139)

Constrained optimization applied to multiscale integrative modeling

Multiscale integrative modeling stands at the intersection between experimental and computational techniques to predict the atomistic structures of important macromolecules. In the integrative modeling process, the experimental information is often integra ...

EPFL2018

Proximity Operators of Discrete Information Divergences

Mireille El Gheche, Giovanni Chierchia

While phi-divergences have been extensively studied in convex analysis, their use in optimization problems often remains challenging. In this regard, one of the main shortcomings of existing methods is that the minimization of phi-divergences is usually pe ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H-infinity Performance

Alireza Karimi, Achille Nicoletti

Recently, a new data-driven method for robust control with H-infinity performance has been proposed. This method is based on convex optimization and converges to the optimal performance when the controller order increases. However, for low-order controller ...

IEEE2018

A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H∞ Performance

Alireza Karimi, Achille Nicoletti

Recently, a new data-driven method for robust control with H∞ performance has been proposed. This method is based on convex optimization and converges to the optimal performance when the controller order increases. However, for low-order controllers, the p ...

Elsevier2018

A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H∞ Performance

Alireza Karimi, Achille Nicoletti

Recently, a new data-driven method for robust control with H ∞ performance has been proposed. This method is based on convex optimization and converges to the optimal performance when the controller order increases. However, for low-order controllers, the ...

2018

Robust and adaptive approaches for Relative Geologic Time Estimation

Mireille El Gheche

For a geoscientist, the Relative Geologic Time (RGT) is an important tool to perform chronostratigraphic analysis. However, automatically estimate an RGT image from a seismic image can be a challenging task where we have to respect seismic features, the de ...

ELSEVIER SCIENCE BV2018

Real-Time Optimizing Control of an Experimental Crosswind Power Kite

Dominique Bonvin, Grégory François, Sean Costello

The contribution of this article is to propose and experimentally validate an optimizing control strategy for power kites flying crosswind. The control strategy provides both path control (stability) and path optimization (efficiency). The path following p ...

Institute of Electrical and Electronics Engineers2018

Diffusion gradient boosting for networked learning

Ali H. Sayed, Bicheng Ying

Using duality arguments from optimization theory, this work develops an effective distributed gradient boosting strategy for inference and classification by networked clusters of learners. By sharing local dual variables with their immediate neighbors thro ...

2017

A Semidefinite Programming Approach to Control Synthesis for Stochastic Reach-Avoid Problems

Maryam Kamgarpour, John Lygeros

We propose a computational approach to approximate the value function and control poli- cies for a finite horizon stochastic reach-avoid problem as follows. First, we formulate an infinite dimensional linear program whose solution characterizes the optimal ...

EPiC Series in Computing2017

A Multilevel Monte Carlo Evolutionary Algorithm for Robust Aerodynamic Shape Design

Fabio Nobile, Pénélope Leyland, Michele Pisaroni

The majority of problems in aircraft production and operation require decisions made in the presence of uncertainty. For this reason aerodynamic designs obtained with traditional deterministic optimization techniques seeking only optimality in a specific s ...

2017

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