activity
20212026
most citedBP-MPC: Optimizing the Closed-Loop Performance of MPC using BackPropagation

1 citations · 1 across the 12 of their papers we have counts for

collaborators
Showing eess.SYShow all

8 papers · 1 filter

eess.SY2026

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…

eess.SY2026

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…

eess.SY2026

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…

eess.SY2025

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…

eess.SY2025

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…

eess.SY2024

Data-Enabled Predictive Iterative Control

Kai Zhang, Riccardo Zuliani, Efe C. Balta +1

This work introduces the Data-Enabled Predictive iteRative Control (DeePRC) algorithm, a direct data-driven approach for iterative LTI systems. The DeePRC learns from previous iter…

eess.SY2024

Closed-loop Performance Optimization of Model Predictive Control with Robustness Guarantees

Riccardo Zuliani, Efe C. Balta, John Lygeros

Model mismatch and process noise are two frequently occurring phenomena that can drastically affect the performance of model predictive control (MPC) in practical applications. We…

eess.SY2021

Batch Model Predictive Control for Selective Laser Melting

Riccardo Zuliani, Efe C. Balta, Alisa Rupenyan +1

Selective laser melting is a promising additive manufacturing technology enabling the fabrication of highly customizable products. A major challenge in selective laser melting is e…