21 citations · 34 across the 47 of their papers we have counts for
12 papers · 1 filter
One-Shot Camera-Based Extrusion Optimization for High Speed Fused Filament Fabrication
Yufan Lin, Xavier Guidetti, Yannick Nagel +2
Off-the-shelf fused filament fabrication 3D printers are widely accessible and convenient, yet they exhibit quality loss at high speeds due to dynamic mis-synchronization between p…
Layer-to-layer Closed-loop Switched Heating and Cooling Control of the Laser Powder Bed Fusion Process
Barış Kavas, Efe C. Balta, Lars Witte +3
This study investigates the stabilization of interlayer temperature in the laser powder bed fusion process through a novel switched layer-to-layer closed-loop feedback controller.…
Closed Loop Reference Optimization for Extrusion Additive Manufacturing
Rawan Hoteit, Andrea Balestra, Nathan Mingard +2
Various defects occur during material extrusion additive manufacturing processes that degrade the quality of the 3D printed parts and lead to significant material waste. This motiv…
Policy Optimization for Unknown Systems using Differentiable Model Predictive Control
Riccardo Zuliani, Efe C. Balta, John Lygeros
Model-based policy optimization often struggles with inaccurate system dynamics models, leading to suboptimal closed-loop performance. This challenge is especially evident in Model…
Guided Multi-Fidelity Bayesian Optimization for Data-driven Controller Tuning with Digital Twins
Mahdi Nobar, Jürg Keller, Alessandro Forino +2
We propose a \textit{guided multi-fidelity Bayesian optimization} framework for data-efficient controller tuning that integrates corrected digital twin simulations with real-world…
Pinet: Optimizing hard-constrained neural networks with orthogonal projection layers
Panagiotis D. Grontas, Antonio Terpin, Efe C. Balta +2
We introduce an output layer for neural networks that ensures satisfaction of convex constraints. Our approach, net, leverages operator splitting for rapid and reliable projecti…
Inside madupite: Technical Design and Performance
Matilde Gargiani, Robin Sieber, Philip Pawlowsky +1
In this work, we introduce and benchmark madupite, a newly proposed high-performance solver designed for large-scale discounted infinite-horizon Markov decision processes with fini…
Wasserstein Distributionally Robust Bayesian Optimization with Continuous Context
Francesco Micheli, Efe C. Balta, Anastasios Tsiamis +1
We address the challenge of sequential data-driven decision-making under context distributional uncertainty. This problem arises in numerous real-world scenarios where the learner…
Iterative Learning Predictive Control for Constrained Uncertain Systems
Riccardo Zuliani, Efe C. Balta, Alisa Rupenyan +1
Iterative learning control (ILC) improves the performance of a repetitive system by learning from previous trials. ILC can be combined with Model Predictive Control (MPC) to mitiga…
madupite: A High-Performance Distributed Solver for Large-Scale Markov Decision Processes
Matilde Gargiani, Robin Sieber, Philip Pawlowsky +2
This paper introduces madupite, a high-performance distributed solver for large-scale Markov Decision Processes (MDPs). MDPs are widely used to model complex dynamical systems in v…
Secure Data Reconstruction: A Direct Data-Driven Approach
Jiaqi Yan, Ivan Markovsky, John Lygeros
This paper addresses the problem of secure data reconstruction for unknown systems, where data collected from the system are susceptible to malicious manipulation. We aim to recove…
Semismooth Newton Methods for Risk-Averse Markov Decision Processes
Matilde Gargiani, Francesco Micheli, Anastasios Tsiamis +1
Inspired by semismooth Newton methods, we propose a general framework for designing solution methods with convergence guarantees for risk-averse Markov decision processes. Our appr…