State Space Models as Foundation Models: A Control Theoretic Overview

1 code implementation • 25 Mar 2024 • Carmen Amo Alonso, Jerome Sieber, Melanie N. Zeilinger

In recent years, there has been a growing interest in integrating linear state-space models (SSM) in deep neural network architectures of foundation models.

Global Performance Guarantees for Localized Model Predictive Control

1 code implementation • 20 Mar 2023 • Jing Shuang Li, Carmen Amo Alonso

We also present an algorithm to determine the communication structure for a given system that will preserve performance while minimizing computational complexity.

Model Predictive Control

Data-driven Distributed and Localized Model Predictive Control

2 code implementations • 22 Dec 2021 • Carmen Amo Alonso, Fengjun Yang, Nikolai Matni

By imposing locality constraints on the system response, we show that the amount of data needed for our synthesis problem is independent of the size of the global system.

Model Predictive Control

Frontiers in Scalable Distributed Control: SLS, MPC, and Beyond

1 code implementation • 3 Oct 2020 • Jing Shuang Li, Carmen Amo Alonso, John C. Doyle

The System Level Synthesis (SLS) approach facilitates distributed control of large cyberphysical networks in an easy-to-understand, computationally scalable way.

Model Predictive Control