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Florin Stoican

Researcher at Politehnica University of Bucharest

Publications -  109
Citations -  1356

Florin Stoican is an academic researcher from Politehnica University of Bucharest. The author has contributed to research in topics: Fault detection and isolation & Fault tolerance. The author has an hindex of 17, co-authored 97 publications receiving 1011 citations. Previous affiliations of Florin Stoican include University of Grenoble & CentraleSupélec.

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Positive invariant sets for fault tolerant multisensor control schemes

TL;DR: This article revisits the construction of ε-approximations of minimal robust positive invariant sets for linear systems upon contractive set-iterations and deals with fault tolerant multisensor control schemes for systems with linear dynamics.
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Advanced UAV-WSN System for Intelligent Monitoring in Precision Agriculture.

TL;DR: A hierarchical structure based on the collaboration between unmanned aerial vehicles (UAVs) and federated wireless sensor networks (WSNs) for crop monitoring in precision agriculture proved to be a robust and efficient solution for data collection, control, analysis, and decisions in such specialized applications.
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A Survey of Collaborative UAV–WSN Systems for Efficient Monitoring

TL;DR: A systematic approach is carried out in order to structure a unitary from conceptual design towards key implementation aspects of UAV–WSN systems, and a research agenda is outlined to advance the field towards tangible economic and social impact.
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Fault tolerant predictive control design for reliable microgrid energy management under uncertainties

TL;DR: In this paper, an extension of a Model Predictive Control (MPC) approach for microgrid energy management is presented, which takes into account electricity costs, power consumption, generation profiles, power and energy constraints as well as uncertainty due to variations in the environment.
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A Collaborative UAV-WSN Network for Monitoring Large Areas.

TL;DR: A hybrid UAV-WSN network which is self-configured to improve the acquisition of environmental data across large areas and shows improvements in both network and data collection efficiency metrics by implementing the proposed algorithms.