8 citations · 12 across the 9 of their papers we have counts for
11 papers
Bilevel MPC for Linear Systems: A Tractable Reduction and Continuous Connection to Hierarchical MPC
Ryuta Moriyasu, Carmen Amo Alonso, Marco Pavone
Model predictive control (MPC) has been widely used in many fields, often in hierarchical architectures that combine controllers and decision-making layers at different levels. How…
Distributed and Localized Model Predictive Control. Part II: Theoretical Guarantees
Carmen Amo Alonso, Jing Shuang Li, Nikolai Matni +1
Engineered cyberphysical systems are growing increasingly large and complex. These systems require scalable controllers that robustly satisfy state and input constraints in the pre…
Data-driven Distributed and Localized Model Predictive Control
Carmen Amo Alonso, Fengjun Yang, Nikolai Matni
Motivated by large-scale but computationally constrained settings, e.g., the Internet of Things, we present a novel data-driven distributed control algorithm that is synthesized di…
Distributed and Localized Model Predictive Control. Part I: Synthesis and Implementation
Carmen Amo Alonso, Jing Shuang Li, James Anderson +1
The increasing presence of large-scale distributed systems highlights the need for scalable control strategies where only local communication is required. Moreover, in safety-criti…
Effective GPU Parallelization of Distributed and Localized Model Predictive Control
Carmen Amo Alonso, Shih-Hao Tseng
To effectively control large-scale distributed systems online, model predictive control (MPC) has to swiftly solve the underlying high-dimensional optimization. There are multiple…
Robust Distributed and Localized Model Predictive Control
Carmen Amo Alonso, Jing Shuang Li, Nikolai Matni +1
We present a robust Distributed and Localized Model Predictive Control (rDLMPC) framework for large-scale structured linear systems. The proposed algorithm uses the System Level Sy…
Distributed Linear Quadratic Regulator Robust to Communication Dropouts
Carmen Amo Alonso, Dimitar Ho, Jose M. Maestre
We present a solution to deal with information package dropouts in distributed controllers for large-scale networks. We do this by leveraging the System Level Synthesis approach, a…
Frontiers in Scalable Distributed Control: SLS, MPC, and Beyond
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. We present an over…
Explicit Distributed and Localized Model Predictive Control via System Level Synthesis
Carmen Amo Alonso, Nikolai Matni, James Anderson
An explicit Model Predictive Control algorithm for large-scale structured linear systems is presented. We base our results on Distributed and Localized Model Predictive Control (DL…
System Level Synthesis via Dynamic Programming
Shih-Hao Tseng, Carmen {Amo Alonso}, SooJean Han
System Level Synthesis (SLS) parametrization facilitates controller synthesis for large, complex, and distributed systems by incorporating system level constraints (SLCs) into a co…
Distributed and Localized Model Predictive Control via System Level Synthesis
Carmen Amo Alonso, Nikolai Matni
We present the Distributed and Localized Model Predictive Control (DLMPC) algorithm for large-scale structured linear systems, wherein only local state and model information needs…