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20162023
most citedImproved uncertainty quantification for neural networks with Bayesian last layer

22 citations · 54 across the 10 of their papers we have counts for

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10 papers · 1 filter

eess.SY2023

Resilient Model Predictive Control of Distributed Systems Under Attack Using Local Attack Identification

Sarah Braun, Sebastian Albrecht, Sergio Lucia

With the growing share of renewable energy sources, the uncertainty in power supply is increasing. In addition to the inherent fluctuations in the renewables, this is due to the th…

eess.SY2022

On the Practical Design of Tube-Enhanced Multi-Stage Nonlinear Model Predictive Control

Sankaranarayanan Subramanian, Yehia Abdelsalam, Sergio Lucia +1

Tube-enhanced multi-stage nonlinear model predictive control is a robust control scheme that can handle a wide range of uncertainties with reduced conservatism and manageable compu…

eess.SY2021

A Polynomial Chaos Approach to Robust Static Output-Feedback Control with Bounded Truncation Error

Yiming Wan, Dongying E. Shen, Sergio Lucia +2

This article considers the static output-feedback control for linear time-invariant uncertain systems with polynomial dependence on probabilistic time-invarian…

eess.SY2020★ 21 cited

Tube-enhanced Multi-stage MPC for Flexible Robust Control of Constrained Linear Systems with Additive and Parametric Uncertainties

Sankaranarayanan Subramanian, Sergio Lucia, Radoslav Paulen +1

The trade-off between optimality and complexity has been one of the most important challenges in the field of robust Model Predictive Control (MPC). To address the challenge, we pr…

eess.SY2020★ 1 cited

On the relationship between data-enabled predictive control and subspace predictive control

Felix Fiedler, Sergio Lucia

Data-enabled predictive control (DeePC) is a recently proposed approach that combines system identification, estimation and control in a single optimization problem, for which only…

eess.SY2020

A Hierarchical Attack Identification Method for Nonlinear Systems

Sarah Braun, Sebastian Albrecht, Sergio Lucia

Many autonomous control systems are frequently exposed to attacks, so methods for attack identification are crucial for a safe operation. To preserve the privacy of the subsystems…