Main Projects

PID-UTN-ENUTNRQ0005536: Modelado de una Microgrid residencial. Estudio de factibilidad y diseño de estrategias de control automático.

UTN, Argentina.

(2019-2021: Head researcher)


PID-UTN-CCUTNRQ0006540: Diseño de algoritmos de inteligencia artificial para reconocimiento de imágenes, con aplicación al pastoreo racional.

UTN, Argentina.

(2019-2021: Head researcher)


PICT-2016-0283: Economic and Stochastic MPC applied to UAVS.

Foncyt, Argentina.

(2017-2020: Head researcher)


PID2019-106212RB-C41: Safe operation of strategic infrastructures based on constrained optimization.

Ministerio de Innovación y Ciencia, España.

(2020-2023: Researcher)


TEC-APQ-03090-17: Robust Control Strategies for convertible UAVs.

FAPEMIG, Brasil.

(2018-2020. Researcher)


PICT-2016-3613: Toolboxes for economic perfomance optimization in refinareis

Foncyt, Argentina.

(2017-2019: Researcher)


CNPq-486440/2013-3: Robust Control Strategies of TiltRotor UAVs for Load Transportation Tasks

CNPq, Brasil.

(2016-2018: Researcher)


DPI 2016: Data-based Economic Optimization in Cyber-Physics Systems.

Ministerio de Economía y Competitividad, Spain.

(2016-2018: Researcher)


TEC-APQ-02903-14: Design of TiltRotor UAVs for Load Transportation and Aerial Manipulation

FAPEMIG, Brasil.

(2016-2018: Researcher)


Development of a toolbox for diagnostics and monitoring of industrial MCP applications.

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(2103-2015. Researcher)

Development of a toolbox for monitoring and evaluation of DMCplus controllers,  to improve the performance of their application at YPF S.A. refineries.


Control and Real Time Optimization in Process Engineering.

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(PIP 2013-2016. Researcher)

The goal of the project is the development of an advanced control toolbox, based on novel results, produced by the members of the group, in the field of MPC, economic optimization, robust control, optimal control.


Real Time Economic Optimization  in MPC applications.

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(CAI+D 2012-2013. Co-Director)

Development of advanced control strategy, mainly MPC, with additional economic objectives. These control strategies focus not only in guaranteeing stability and feasibility, but mainly in optimizing the economic performance of the plant, without producing and excessively high computational burden.


Hyghly-Complex and Networked Control Systems (HYCON2).

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(European Union, FP7. 2010-2014. Researcher)

The aim of this project is to stimulate and establish a long-term integration in the strategic field of control of complex, large-scale, and networked dynamical systems. It focuses in particular on the domains of ground and aerospace transportation, electrical power networks, process industries, and biological and medical systems.


Networked MPC.

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(European Union. ERDF. 2009-2013. Researcher)

Development of advanced control strategies for networked distributed applications.


 

Hybrid Control: Taming Heterogeneity and Complexity of Networked Embedded Systems (HYCON).

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(European Union. FP7. 2004-2008. Researcher)

The main objective of the NoE HYCON is to establish a durable community of leading researchers and practitioners who develop and apply the hybrid systems approach to networked embedded control systems.Hybrid systems provide an emergent scientific paradigm to systematically address the analysis, modelling,simulation, synthesis, and optimisation of digital technology that controls physical devices and communicates directly or via networks with other computerized systems and with human users and supervisors.