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Mostrando ítems 11-18 de 18
Artículo
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A deep learning-based strategy for fault detection and isolation in parabolic-trough collectors
(Elsevier, 2022-03)
Solar plants are exposed to the appearance of faults in some of their components, as they are vulnerable to the action of external agents (wind, rain, dust, birds …) and internal defects. However, it is necessary to ensure ...
Ponencia
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Multi-Vehicle System Localization by Distributed Moving Horizon Estimation over a Sensor Network with Sporadic Measurements
(Elsevier, 2022)
This paper proposes a Distributed Moving Horizon Estimator (DMHE) for the Multi-Vehicle system localization problem using Sensor Networks with sporadic measurements. Due to its capability to efficiently exploit environmental ...
Artículo
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Distributed model predictive control for tracking: a coalitional clustering approach
(IEEE, 2022-12)
In this article, a coalitional robust model predictive controller for tracking target sets is presented. The overall system is controlled by a set of local control agents that dynamically merge into cooperative coalitions ...
Artículo
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Market-based clustering of model predictive controllers for maximizing collected energy by parabolic-trough solar collector fields
(Elsevier, 2022)
This article focuses on maximizing the thermal energy collected by parabolic-trough solar collector fields to increase the production of the plant. To this end, we propose a market-based clustering model predictive control ...
Artículo
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Fast clustering for multi-agent model predictive control
(IEEE, 2022-09)
In coalitional model predictive control, the overall system is controlled by a set of networked agents that are dynamically arranged into clusters of connected agents that coordinate their actions, also called coalitions. ...
Artículo
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Nonlinear model predictive control for thermal balance in solar trough plants
(Elsevier, 2022-09)
The size of existing commercial solar trough plants poses new challenges in applying advanced control strategies to optimize operation. One of these challenges is to obtain a better thermal balance of the loops’ temperature. ...
Ponencia
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Collaborative learning model predictive control for repetitive tasks
(IEEE, 2022-12)
This paper presents a cloud-based learning model predictive controller that integrates three interacting components: a set of agents, which must learn to perform a finite set of tasks with the minimum possible local cost; ...
Ponencia
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Fault Detection and Isolation Based on Deep Learning for a Fresnel Collector Field
(IFAC Publisher ; Elsevier, 2022)
With the advancement of new technologies, power systems are increasingly equipped with more sensors and actuators, heightening the risk of failure. This fact, together with the vulnerability of solar plants -not only to ...