24 papers
A graph-informed regret metric for optimal distributed control
Daniele Martinelli, Andrea Martin, Giancarlo Ferrari-Trecate +1
We consider the optimal control of large-scale systems using distributed controllers whose network topology mirrors the coupling graph between subsystems. In this work, we introduc…
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…
Sinkhorn Ambiguity Sets for Distributionally Robust Control: Convexity, Weak Compactness, and Tractability
Riccardo Cescon, Andrea Martin, Giancarlo Ferrari-Trecate
Classical stochastic control assumes perfect knowledge of the uncertainty affecting the plant. In practice, however, such information is often incomplete. To address this limitatio…
Data-Driven Optimal Distributed Controller Synthesis via Spatial Regret
Vaibhav Gupta, Daniele Martinelli, Giancarlo Ferrari-Trecate +2
In this paper, we present a novel method for synthesising an optimal distributed spatial regret controller using experimentally obtained frequency-response data. Spatial regret pro…
L2RU: a Structured State Space Model with prescribed L2-bound
Leonardo Massai, Muhammad Zakwan, Giancarlo Ferrari-Trecate
Structured state-space models (SSMs) have recently emerged as a powerful architecture at the intersection of machine learning and control, featuring layers composed of discrete-tim…
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…