Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Daniel E. Ochoa"'
Autor:
Daniel E. Ochoa, Felipe Galarza-Jimenez, Felipe Wilches-Bernal, David A. Schoenwald, Jorge I. Poveda
Publikováno v:
IEEE Access, Vol 11, Pp 20560-20581 (2023)
Virtual Power Plants (VPPs) have emerged as a modern real-time energy management architecture that seeks to synergistically coordinate an aggregation of renewable and non-renewable generation systems to overcome some of the fundamental limitations of
Externí odkaz:
https://doaj.org/article/e0e8c8582ccc4dbab0011529da680c2e
Publikováno v:
IEEE Access, Vol 8, Pp 173227-173238 (2020)
This paper investigates the combination of reinforcement learning and neural networks applied to the data-driven control of dynamical systems. In particular, we propose a multi-critic actor-critic architecture that eases the value function learning t
Externí odkaz:
https://doaj.org/article/0354c269f2bc4e5eb256431311701bea
Publikováno v:
IEEE Control Systems Letters. 5:301-306
We present a new class of accelerated distributed algorithms for the robust solution of convex optimization problems over networks. The novelty of the approach lies in the introduction of distributed restarting mechanisms that coordinate the evolutio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9485c2221ee601842c0ebd8b111d7443
https://doi.org/10.1109/lcsys.2020.3001632
https://doi.org/10.1109/lcsys.2020.3001632
Autor:
Daniel E. Ochoa, Jorge I. Poveda
Traffic congestion has dire economic and social impacts in modern metropolitan areas. To address this problem, in this paper we introduce a novel type of model-free transactive controllers to manage vehicle traffic in highway networks for which preci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::736573d8507a6d8fa1c5eabb3c757788
http://arxiv.org/abs/2204.09835
http://arxiv.org/abs/2204.09835
Autor:
Daniel E. Ochoa, Jorge I. Poveda
We introduce a new closed-loop architecture for the online solution of approximate optimal control problems in the context of continuous-time systems. Specifically, we introduce the first algorithm that incorporates dynamic momentum in actor-critic s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6ae1a71292de7d3161f212b3c84c143
Publikováno v:
IEEE Access, Vol 8, Pp 173227-173238 (2020)
This paper investigates the combination of reinforcement learning and neural networks applied to the data-driven control of dynamical systems. In particular, we propose a multi-critic actor-critic architecture that eases the value function learning t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a09dfbf6accc10b874bb24004caa4b9
https://ieeexplore.ieee.org/document/9200594/
https://ieeexplore.ieee.org/document/9200594/
Publikováno v:
CAADCPS@CPSIoTWeek
The area of Cyber-Physical Systems (CPS) has emerged as a general discipline that studies complex dynamical systems that incorporate computation, control, and communication technologies [10]. The application of CPS spans several domains, from autonom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cda3331b0401e170594f266ce0dd90a8
https://doi.org/10.1145/3457335.3461710
https://doi.org/10.1145/3457335.3461710
Publikováno v:
CDC
We study the problem of robust resource allocation with momentum following a dynamical systems point of view. Motivated by a class of existing optimization dynamics with no momentum defined on the general m-simplex, we propose a class of time-varying
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31f31fc1083e9222055f22393571d5eb
https://doi.org/10.1109/cdc40024.2019.9028936
https://doi.org/10.1109/cdc40024.2019.9028936
Publikováno v:
Digital.CSIC. Repositorio Institucional del CSIC
instname
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
ACC
instname
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
ACC
Trabajo presentado en la American Control Conference (ACC), celebrada en Philadelphia (Estados Unidos), del 10 al 12 de julio de 2019
A hierarchical control strategy is proposed to solve the optimal drainage problem in sewer systems by combining
A hierarchical control strategy is proposed to solve the optimal drainage problem in sewer systems by combining
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::321eadd77adba5c48df6516992b85a04
http://hdl.handle.net/10261/206659
http://hdl.handle.net/10261/206659
Publikováno v:
Journal of Automation and Control Engineering. :213-219
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ff694286160483eb76baa26da7d4f6a
https://doi.org/10.18178/joace.4.3.213-219
https://doi.org/10.18178/joace.4.3.213-219