19 papers
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…
SDNator is Not Another SDN Controller: Enabling Extensible Data-Driven Control in Cyber-Physical Systems
Y. Lin, R. Zhang, E. Balta +5
An SDN-like centralized control architecture is increasingly popular and has been widely explored in cyber-physical systems (CPS) such as manufacturing, internet-of-things, and aut…
Deep Reinforcement Learning for Flexible Job Shop Scheduling with Random Job Arrivals
Yu Tang, Muhammad Zakwan, Efe Balta +2
The Flexible Job Shop Scheduling Problem (FJSP) is the optimal allocation of a set of jobs to machines. Two primary challenges persist in FJSP: the unpredictable arrival of future…
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…