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Daniel Sbarbaro

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

13

Venues

5

Active years

2004–2023

Best venue rank

C

Where they publish

Papers

13 indexed papers, newest first.

YearVenueTitleAuthors
2023CoDITGeneralized Predictive Proportional Integral Controller Design for Unstable Plant Models with Long-Dead Times.Alejandro J. Rojas, Daniel Sbarbaro
2023CoDITAdaptive Kalman Filter for On-Line Spectroscopic Sensor Corrections.Daniel Sbarbaro, Tor Arne Johansen, Jorge Yaez
2021IECONTopologies and Control Strategies of Partial Power DC/DC Converters for Photovoltaic Systems.Nicolas Weldt, Jos R. Espinoza, Daniel Sbarbaro, Luis Morn, Samir Kouro
2020IECONFast-Model Predictive Control for a Grid-Tie Photovoltaic System.Jos J. Silva, Jos R. Espinoza, Luis Morn, Daniel Sbarbaro, Jaime Addin Rohten, Miguel A. Torres, Rodrigo Mndez
2019IECONFast MPC Algorithm for a Grid Tied Photovoltaic System based on a Multilevel Inverter.Jos J. Silva, Jos R. Espinoza, Daniel Sbarbaro, Luis Morn, Jaime Addin Rohten, Luis Vaccaro
2016IECONDynamic output power optimization in hybrid PV/T panels.Daniel Sbarbaro, Rubn Pea
2013IECONComparative analysis of manifold learning algorithms for tomographic sensor processing.Cristian Morales, Fernando Lotero, Daniel Sbarbaro
2013IECONPredictive control for static power converters working in wide frequency ranges.Jaime Addin Rohten, Jos R. Espinoza, Felipe Villarroel, Javier A. Muoz, Carlos R. Baier, Pedro E. Melin, Daniel Sbarbaro
2007ISNNAutomatic Diagnosis of Foot Plant Pathologies: A Neural Networks Approach.Marco Mora, Mary Carmen Jarur, Daniel Sbarbaro, Leopoldo Pavesi
2006ICANNDual Adaptive ANN Controllers Based on Wiener Models for Controlling Stable Nonlinear Systems.Daniel Sbarbaro
2005CIARPA Robust Footprint Detection Using Color Images and Neural Networks.Marco Mora, Daniel Sbarbaro
2005ICANNSupervision of Control Valves in Flotation Circuits Based on Artificial Neural Network.Daniel Sbarbaro, Gonzalo Carvajal
2004ISNNMultivariable Generalized Minimum Variance Control Based on Artificial Neural Networks and Gaussian Process Models.Daniel Sbarbaro, Roderick Murray-Smith, Arturo Valdes