Declaración 23-001-CD

@article{Saavedra2025,

title = {Comparative evaluation of data-based estimators for wave-induced force in wave energy converters},

author = {M. Saavedra and N. Faedo and F. Inthamoussou and F. Mosquera and F. Garelli},

doi = {10.1007/s40722-025-00427-4},

issn = {2198-6452},

year  = {2025},

date = {2025-09-01},

urldate = {2025-09-01},

journal = {J. Ocean Eng. Mar. Energy},

publisher = {Springer Science and Business Media LLC},

abstract = {<jats:title>Abstract</jats:title>

          <jats:p>Wave energy conversion technology emerges as a promising approach to renewable energy generation, offering a consistent and predictable power source that complements intermittent renewable energy sources such as solar and wind power. Achieving optimal ocean wave energy absorption requires precise knowledge of the so-called wave excitation force, which is typically estimated through model-based techniques reliant on accurate system descriptions. However, uncertainties inherent to hydrodynamic modelling often limit the reliability of these approaches. To address this challenge, this paper presents a comprehensive evaluation of model-free data-based estimators, for wave excitation torque estimation in Wavestar like wave energy converters (WECs). The study examines various neural network architectures, including static models (feedforward networks) and those incorporating temporal dynamics (recurrent neural networks and long short-term memory networks). The analysis examines the impact of utilising multiple input combinations, ranging from motion variables to configurations enhanced with surrounding wave height measurements from the device’s vicinity. Input selection is guided by correlation analysis and spectral coherence evaluation to ensure physical relevance and practical feasibility. Estimators are trained and tested using experimental data obtained from a comprehensive wave tank campaign emulating diverse sea state conditions. The results demonstrate that architectures incorporating temporal considerations achieve superior performance, particularly under wide-banded sea states. A comparative analysis with a model-based estimator, implemented via a Kalman–Bucy Filter with a harmonic oscillator expansion, highlights the advantages of neural networks, especially under challenging conditions where model-based approaches face significant limitations. These findings underscore the capability of data-based strategies to reduce dependence on potentially complex and uncertain analytical models, offering a promising alternative for improving WEC control systems.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1111/aor.15064,

title = {Switched Controllers in Fully Closed Loop Insulin Delivery Systems: Reducing the Trade-Off Between Prandial Control and Safety},

author = { F. L. Da Rosa Jurao and E. Fushimi and F. Garelli},

url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/aor.15064},

doi = {https://doi.org/10.1111/aor.15064},

year  = {2025},

date = {2025-08-02},

urldate = {2025-08-02},

journal = {Artificial Organs},

volume = {n/a},

number = {n/a},

abstract = {ABSTRACT Background One of the main challenges in control algorithm design for full closed-loop automated insulin delivery systems is the trade-off between the effective compensation of meal-related disturbances and ensuring user safety during the postprandial and fasting periods. Methods This paper proposes and evaluates the performance of a switched tuning strategy, a promising but relatively underexplored solution in this domain. This method employs two distinct tunings of a primary control algorithm: an aggressive tuning for meal compensation and a conservative tuning for fasting periods. The analysis considers implementing the switched strategy for three control algorithms: model predictive control and proportional-derivative control, both widely used for glucose regulation, and a linear quadratic Gaussian control, an optimal algorithm previously validated in clinical settings under a switched structure. Additionally, to obtain a more comprehensive understanding of the switched strategy implications, two nonswitched controllers are implemented for each control algorithm: an aggressive and a conservative tuning strategy. Results The switched strategy significantly improves the trade-off between meal compensation and safety, increasing the time within the target range of 70–180 [mg/dL] for all three algorithms. For proportional-derivative control, the time in range increases from 69.1% with the conservative tuning and 83.1% with the aggressive to 86.6% with the switched structure. For model predictive control, the improvement is from 73.4% and 74.1% to 85.8%. Last, linear quadratic Gaussian control increases from 65.0% and 70.4% to 85.6%. Conclusion The findings suggest that the switched strategy may be a feasible and straightforward approach for enhancing meal compensation without increasing the risk of postprandial hypoglycemia in people with diabetes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1177/29941520251358842,

title = {Identification of Physical Activity Type in People with Diabetes: A Spectrogram-Based Approach},

author = { M. Saavedra and F. Inthamoussou and E. Fushimi and F. Garelli},

url = {https://www.liebertpub.com/doi/abs/10.1177/29941520251358842},

doi = {10.1177/29941520251358842},

year  = {2025},

date = {2025-07-21},

urldate = {2025-01-01},

journal = {Diabetes Technology and Obesity Medicine},

volume = {1},

number = {1},

pages = {361-373},

abstract = {Background: Individuals with type 1 diabetes (T1D) require close glucose monitoring to prevent both short- and long-term complications. Physical activity (PA) is a significant source of variability in metabolic dynamics, leading to glycemic fluctuations that depend on the type, intensity, and duration of the exercise. Accurately monitoring and classifying the type of PA is crucial for optimizing glycemic control and minimizing the risk of hypoglycemia. Method: This study utilizes the largest clinical trial of PA in people with T1D to date, the Type 1 Diabetes and Exercise Initiative (T1DEXI), which included both structured and unstructured PA sessions, to develop an online classification approach for identifying the type of PA (aerobic, interval, resistance). A computationally efficient convolutional neural network (CNN) was trained on time–frequency representations (spectrograms) of step count and heart rate signals, readily available from wearable devices, from the structured PA sessions of the T1DEXI dataset. The proposed methodology presents an ad hoc process for designing the spectrograms based on the CNN architecture to optimize the classifier’s performance. Results: The CNN-based classification approach was implemented using spectrograms of 5- and 30-min signals, resulting in two classifiers that achieve high classification accuracy when evaluated on the structured PA sessions. The 5-min classifier was then applied to unstructured PA sessions, where the predicted distribution of glucose changes for the activity types was consistent with clinical evidence. Conclusion: These results demonstrate the potential of the proposed approach for its integration into decision support systems or automated insulin delivery systems, enabling improved glucose management during exercise in T1D.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1016/j.ymssp.2025.112323,

title = {Experimental investigation of wave-to-force modelling uncertainty for wave energy converters},

author = {M. Celesti and G. Papini and E. Pasta and Y. Peña-Sanchez and F. Mosquera and F. Ferri and N. Faedo},

doi = {10.1016/j.ymssp.2025.112323},

year  = {2025},

date = {2025-01-01},

journal = {Mechanical Systems and Signal Processing},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1016/j.bbe.2025.05.004,

title = {Robust dual-hormone controller for full closed-loop glucose regulation in people with type 1 diabetes: An in silico study},

author = {E. Fushimi and F. Bianchi and H. De Battista and F. Garelli},

doi = {10.1016/j.bbe.2025.05.004},

year  = {2025},

date = {2025-01-01},

journal = {Biocybernetics and Biomedical Engineering},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1109/tbme.2025.3530711,

title = {Personalized Model Identification for Glucose Dynamics from Clinical Data with Incomplete Inputs},

author = {B. Ozaslan and E. Aiello and E. Fushimi and F. Doyle and E. Dassau},

doi = {10.1109/tbme.2025.3530711},

year  = {2025},

date = {2025-01-01},

journal = {IEEE Transactions on Biomedical Engineering},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1016/j.compbiomed.2025.110223,

title = {Population-optimized electrode montage approximates individualized optimization in transcranial temporal interference stimulation},

author = {K. Yatsuda and M. Fernández-Corazza and W. Yu and J. Gomez-Tames},

doi = {10.1016/j.compbiomed.2025.110223},

year  = {2025},

date = {2025-01-01},

journal = {Computers in Biology and Medicine},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1088/1741-2552/adab20,

title = {Electrical impedance tomography meets reduced order modelling: a framework for faster and more reliable electrical conductivity estimations},

author = {M. Walker and M. Fernández-Corazza and S. Turovets and L. Beltrachini},

doi = {10.1088/1741-2552/adab20},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Neural Engineering},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.3390/fermentation11060354,

title = {Enhancement of Lipid Production in Rhodosporidium toruloides: Designing Feeding Strategies Through Dynamic Flux Balance Analysis},

author = {M. Castañeda and S. Nuñez and M. Jamilis and H. De Battista},

doi = {10.3390/fermentation11060354},

year  = {2025},

date = {2025-01-01},

journal = {Fermentation},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1109/jsen.2024.3486534,

title = {Design of a Novel Very-Low Input Capacitance High-Bandwidth Buffer for a Biomass Sensor},

author = {F. Amor and M. Haberman and M. Jamilis and F. Guerrero and H. De Battista},

doi = {10.1109/jsen.2024.3486534},

year  = {2025},

date = {2025-01-01},

journal = {IEEE Sensors Journal},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.3390/chips4020027,

title = {Enhancing CMRR in Fully Differential Amplifiers via Power Supply Bootstrapping},

author = {E. Spinelli and V. Catacora and F. Guerrero and M. Haberman},

doi = {10.3390/chips4020027},

year  = {2025},

date = {2025-01-01},

journal = {Chips},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1109/cdc56724.2024.10886157,

title = {Homogeneous Filtering Unknown Input Observer for Wave Energy Applications},

author = {P. Fornaro and F. Mosquera and P. Puleston and C. Evangelista and J. Ringwood},

doi = {10.1109/cdc56724.2024.10886157},

year  = {2024},

date = {2024-01-01},

journal = {2024 IEEE 63rd Conference on Decision and Control (CDC)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.3390/proceedings2024097014,

title = {A Transformer-Based Front-End Circuit for Grounded Capacitive Sensors with Square-Wave Excitation},

author = {M. Haberman and E. Spinelli and F. Reverter},

doi = {10.3390/proceedings2024097014},

year  = {2024},

date = {2024-01-01},

journal = {Proceedings},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.23919/ecc64448.2024.10590991,

title = {Hybrid Optimal Control for an Active Mechanical Motion Rectifier for Wave Energy Converters via Separation Principle},

author = {P. Fornaro and J. Ringwood},

doi = {10.23919/ecc64448.2024.10590991},

year  = {2024},

date = {2024-01-01},

journal = {2024 European Control Conference (ECC)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.23919/acc60939.2024.10644342,

title = {On the Controllability of an Active Mechanical Motion Rectifier for Wave Energy Converters},

author = {P. Fornaro and J. Ringwood},

doi = {10.23919/acc60939.2024.10644342},

year  = {2024},

date = {2024-01-01},

journal = {2024 American Control Conference (ACC)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1109/ccta60707.2024.10666656,

title = {A Sliding Mode-Based Tracking Observer for Excitation Force Estimation in Wave Energy Systems},

author = {F. Mosquera and P. Fornaro and P. Puleston and C. Evangelista and J. Ringwood},

doi = {10.1109/ccta60707.2024.10666656},

year  = {2024},

date = {2024-01-01},

journal = {2024 IEEE Conference on Control Technology and Applications (CCTA)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1089/dia.2023.0528,

title = {Online Classification of Unstructured Free-Living Exercise Sessions in People with Type 1 Diabetes},

author = {E. Fushimi and E. Aiello and S. Cho and M. Riddell and R. Gal and C. Martin and S. Patton and M. Rickels and I. Francis J. Doyle},

doi = {10.1089/dia.2023.0528},

year  = {2024},

date = {2024-01-01},

journal = {Diabetes Technology & Therapeutics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1002/bit.28579,

title = {Computational assessment of lipid production in Rhodosporidium toruloides in two‐stage and one‐stage batch bioprocesses},

author = {M. Castañeda and S. Nuñez and M. Jamilis and H. De Battista},

doi = {10.1002/bit.28579},

year  = {2024},

date = {2024-01-01},

journal = {Biotechnology and Bioengineering},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1016/j.conengprac.2023.105818,

title = {Experimental assessment of combined sliding mode & moment-based control (SM2C) for arrays of wave energy conversion systems},

author = {N. Faedo and F. Mosquera and E. Pasta and G. Papini and Y. Peña-Sanchez and C. Evangelista and F. Ferri and J. Ringwood and P. Puleston},

doi = {10.1016/j.conengprac.2023.105818},

year  = {2024},

date = {2024-01-01},

journal = {Control Engineering Practice},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1109/tste.2023.3320190,

title = {An Anti-Windup Mechanism for State Constrained Linear Control of Wave Energy Conversion Systems: Design, Synthesis, and Experimental Assessment},

author = {N. Faedo and F. Carapellese and G. Papini and E. Pasta and F. Mosquera and F. Ferri and T. Brekken},

doi = {10.1109/tste.2023.3320190},

year  = {2024},

date = {2024-01-01},

journal = {IEEE Transactions on Sustainable Energy},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1016/j.conengprac.2024.105949,

title = {Data-based modelling of arrays of wave energy systems: Experimental tests, models, and validation},

author = {E. Pasta and G. Papini and Y. Peña-Sanchez and F. Mosquera and F. Ferri and N. Faedo},

doi = {10.1016/j.conengprac.2024.105949},

year  = {2024},

date = {2024-01-01},

journal = {Control Engineering Practice},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1016/j.conengprac.2024.106019,

title = {Assessment and validation of wave excitation force estimators in operative conditions},

author = {G. Papini and E. Pasta and Y. Peña-Sanchez and F. Mosquera and D. García-Violini and F. Ferri and N. Faedo},

doi = {10.1016/j.conengprac.2024.106019},

year  = {2024},

date = {2024-01-01},

journal = {Control Engineering Practice},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1080/10255842.2023.2241945,

title = {Auto adaptation of closed-loop insulin delivery system using continuous reward functions and incremental discretization},

author = {M. C. Serafini and N. Rosales and F. Garelli},

doi = {10.1080/10255842.2023.2241945},

year  = {2024},

date = {2024-01-01},

journal = {Computer Methods in Biomechanics and Biomedical Engineering},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1109/tste.2023.3343995,

title = {Wave Energy Optimal Control Structure With Second-Order Sliding Mode Tracking: Hardware-in-the-Loop Assessment},

author = {F. Mosquera and N. Faedo and C. Evangelista and J. Ringwood and P. Puleston},

doi = {10.1109/tste.2023.3343995},

year  = {2024},

date = {2024-01-01},

journal = {IEEE Transactions on Sustainable Energy},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.3390/jcm13113084,

title = {Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans},

author = {J. Gomez-Tames and M. Fernández-Corazza},

doi = {10.3390/jcm13113084},

year  = {2024},

date = {2024-01-01},

journal = {Journal of Clinical Medicine},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1080/02656736.2024.2364721,

title = {Impact of surrounding tissue-type and peri-electrode gap in stereoelectroencephalography guided (SEEG) radiofrequency thermocoagulation (RF-TC): a computational study},

author = {S. Collavini and J. Pérez and E. Berjano and M. Fernández-Corazza and S. Oddo and R. Irastorza},

doi = {10.1080/02656736.2024.2364721},

year  = {2024},

date = {2024-01-01},

journal = {International Journal of Hyperthermia},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1016/j.phycom.2024.102419,

title = {A comparison between autocorrelation- and crosscorrelation-based coarse frame synchronization schemes for OFDM-PLC systems},

author = {M. Colombo and J. Ureña and Á. Hernández and C. Marziani and M. Mayosky},

doi = {10.1016/j.phycom.2024.102419},

year  = {2024},

date = {2024-01-01},

journal = {Physical Communication},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1103/physreva.110.042219,

title = {Quantum and classical dynamics correspondence and the brachistochrone problem},

author = {H. Fanchiotti and C. García Canal and M. Mayosky and A. Pérez and A. Veiga},

doi = {10.1103/physreva.110.042219},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Physical Review A},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1063/5.0216741,

title = {Model-free dynamic estimation of fore-aft and side-to-side wind turbine tower deflections},

author = {M. Saavedra and F. Inthamoussou and F. Garelli},

doi = {10.1063/5.0216741},

year  = {2024},

date = {2024-01-01},

journal = {Journal of Renewable and Sustainable Energy},

keywords = {},

pubstate = {published},

tppubtype = {article}

}