no code implementations • 5 Sep 2018 • Erfan Nozari, Jorge Cortés
Goal-driven selective attention (GDSA) refers to the brain's function of prioritizing the activity of a task-relevant subset of its overall network to efficiently process relevant information while inhibiting the effects of distractions.
no code implementations • 5 Sep 2018 • Erfan Nozari, Jorge Cortés
Goal-driven selective attention (GDSA) is a remarkable function that allows the complex dynamical networks of the brain to support coherent perception and cognition.
1 code implementation • 15 Mar 2020 • Francesca Boso, Dimitris Boskos, Jorge Cortés, Sonia Martínez, Daniel M. Tartakovsky
This study focuses on the latter step by investigating the spatio-temporal evolution of data-driven ambiguity sets and their associated guarantees when the random QoIs they describe obey hyperbolic partial-differential equations with random inputs.
Optimization and Control Analysis of PDEs
no code implementations • 13 May 2020 • Masih Haseli, Jorge Cortés
We identify conditions on the network topology to ensure the algorithm identifies the maximal Koopman-invariant subspace in the span of the original dictionary, characterize its time, computational, and communication complexity, and establish its robustness against communication failures.
no code implementations • 3 Nov 2020 • Kehan Long, Cheng Qian, Jorge Cortés, Nikolay Atanasov
Control barrier functions are widely used to enforce safety properties in robot motion planning and control.
Motion Planning Robotics
no code implementations • 8 Aug 2021 • Masih Haseli, Jorge Cortés
This paper tackles the data-driven approximation of unknown dynamical systems using Koopman-operator methods.
no code implementations • 3 Jan 2022 • Michael McCreesh, Jorge Cortés
Neuroscientific evidence shows that for most brain networks all pathways between cortical regions either pass through the thalamus or a transthalamic parallel route exists for any direct corticocortical connection.
no code implementations • 1 May 2022 • Yan Jiang, Wenqi Cui, Baosen Zhang, Jorge Cortés
Specifically, we use RL to learn a neural network-based control policy mapping from the integral variables of DAI to the controllable power injections which provides optimal transient frequency control, while DAI inherently ensures the frequency restoration and optimal economic dispatch.
no code implementations • 15 Jul 2022 • Masih Haseli, Jorge Cortés
Extended Dynamic Mode Decomposition (EDMD) is a popular data-driven method to approximate the action of the Koopman operator on a linear function space spanned by a dictionary of functions.
no code implementations • 19 Aug 2022 • Guido Cavraro, Zhenyi Yuan, Manish K. Singh, Jorge Cortés
This paper considers the problem of voltage regulation in distribution networks.
no code implementations • 26 Sep 2022 • Zhenyi Yuan, Guido Cavraro, Manish K. Singh, Jorge Cortés
We identify the conditions on the surrogates and control parameters to ensure that the locally acting controllers collectively converge, in a global asymptotic sense, to a DN operating point agreeing with the local surrogates.
no code implementations • 20 Mar 2023 • Jie Feng, Wenqi Cui, Jorge Cortés, Yuanyuan Shi
Deep reinforcement learning approaches are becoming appealing for the design of nonlinear controllers for voltage control problems, but the lack of stability guarantees hinders their deployment in real-world scenarios.
no code implementations • 15 May 2023 • Yan Jiang, Wenqi Cui, Baosen Zhang, Jorge Cortés
Existing settings of decentralized learning either require players to have full information or the system to have certain special structure that may be hard to check and hinder their applicability to practical systems.
no code implementations • 7 Jun 2023 • Zhenyi Yuan, Guido Cavraro, Jorge Cortés
We consider the problem of learning local Volt/Var controllers in distribution grids (DGs).
no code implementations • 30 Aug 2023 • Miguel Vaquero, Jorge Cortés, David Martín de Diego
This work presents a general geometric framework for simulating and learning the dynamics of Hamiltonian systems that are invariant under a Lie group of transformations.
no code implementations • 9 Feb 2024 • Pol Mestres, Carlos Nieto-Granda, Jorge Cortés
This paper proposes a distributed controller synthesis framework for safe navigation of multi-agent systems.
no code implementations • 17 Mar 2024 • Zhenyi Yuan, Guido Cavraro, Ahmed S. Zamzam, Jorge Cortés
In the context of managing distributed energy resources (DERs) within distribution networks (DNs), this work focuses on the task of developing local controllers.