1 citations · 4 across the 22 of their papers we have counts for
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Model-Agnostic Meta Learning for Differentiable MPC
Salma Elfeki, Riccardo Zuliani, Niklas Schmid +2
Applying policy optimization to Model Predictive Control (MPC) yields high-performance and reliable controllers. However, the resulting controllers often overfit their training con…
Multi-scale closed-loop melt pool control for LPBF via policy optimization
Junan Lin, Riccardo Zuliani, Baris Kavas +3
Laser powder bed fusion (LPBF) is a metal additive manufacturing process where temperature stabilization is of vital importance to avoid defects such as distortion and cracking. Ex…
Free Parametrization of L_2-Bounded Structured State-Space Controllers for Nonlinear Control with Stability Guarantees
Muhammad Zakwan, Leonardo Massai, Efe C. Balta +1
Designing stabilizing control policies for nonlinear systems while optimizing complex objectives remains a formidable challenge. Neural networks (NNs), despite their expressive pow…
Controller Design for Structured State-space Models via Contraction Theory
Muhammad Zakwan, Vaibhav Gupta, Alireza Karimi +2
This paper presents an indirect data-driven output feedback controller synthesis for nonlinear systems, leveraging Structured State-space Models (SSMs) as surrogate models. SSMs ha…
Policy Optimization with Differentiable MPC: Convergence Analysis under Uncertainty
Riccardo Zuliani, Efe C. Balta, John Lygeros
Model-based policy optimization is a well-established framework for designing reliable and high-performance controllers across a wide range of control applications. Recently, this…
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…