Artículos de publicaciones periódicas

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Active noise hybrid time-varying control for motorcycle helmets
(2010-05) Castañé-Selga, Rosa; Sánchez-Peña, Ricardo
"Recent noise at work regulations in the EU (2003) have been established to prevent noise induced hearing loss (NIHL). This imposes better performance results to traditional feedback active noise control (ANC) in motorcycle helmets, which suffer from well known limitations. Here two new ideas are applied to this problem. First, an hybrid (feedforward/feedback) linear time invariant (LTI) controller is designed for a motorcycle helmet ANC, which improves the resulting attenuation. This is achieved by adding an extra pair of microphones which measure the external noise that is then used as the feedforward input signal. In addition and to increase even more the resulting performance, the air velocity is measured in real-time and used as the parameter which schedules a linear parameter varying (LPV) feedback (FB) controller. This is combined with the previous feedforward (FF) controller, resulting in a time-varying hybrid controller. Both hybrid, LTI and LPV controllers are designed using linear matrix inequality (LMI)-based optimization. Two experiments have been carried out to measure the relation between external noise spectra and velocity: a wind tunnel test and a freeway ride experience. The resulting controllers are tested in a simulation which uses actual data obtained from the freeway experiment. The resulting attenuations in this motivating study seem promising for future controller tests to be performed in real-time, with the adequate hardware."
Advances in alkaline water electrolyzers: a review
(2019-06) David, Martín Rafael; Ocampo-Martínez, Carlos; Sánchez-Peña, Ricardo
"The renewed concern for the care of the environment has led to lower emissions of greenhouse gases without sacrificing modern comforts. Widespread proposal focuses on energy produced from renewable sources and its subsequent storage and transportation based on hydrogen. Currently, this gas applies to the chemical industry and its production is based on fossil fuels. The introduction of this energy vector requires the development of environmental-friendly methods for obtaining it. In this paper, existing techniques are just presented and the main focus is made on electrolysis, a mature procedure. In turn, some developed proposals as previous steps to the hydrogen economy are presented. Finally, some lines of research to improve alkaline electrolysis technology are commented."
Applied LPV Control with Full Block Multipliers and Regional Pole Placement
(2010-05) Sánchez-Peña, Ricardo; Ghersin, Alejandro S.
"A formulation of an LPV control problem with regional pole placement constraints is presented, which is suitable for the application of a Full Block S-Procedure. It is demonstrated that improved bounds can be obtained on the induced 𝐿2 norm of closed loop systems, while satisfying pole placement constraints. An application consisting in the 6 degrees of freedom (DOF) control of a space vehicle is developed as an example, with hardware in the loop (HIL) simulation. This shows that the method is appealing from the practical point of view, considering that the synthesized control law can be implemented satisfactorily in standard flight control systems. Conclusions with remarks towards the practical use of the method are presented as well."
Artificial pancreas: clinical study in Latin America without premeal insulin boluses
(2018-09) Sánchez-Peña, Ricardo; Colmegna, Patricio; Garelli, Fabricio; De Battista, Hernán; García Violini, Demián; Moscoso-Vásquez, Marcela; Rosales, Nicolás; Fushimi, Emilia; Campos-Náñez, Enrique; Breton, Marc; Beruto, Valeria; Scibona, Paula; Rodriguez, Cintia; Giunta, Javier; Simonovich, Ventura; Belloso, Waldo H.; Cherñavvsky, Daniel; Grosembacher, Luis
"Background: Emerging therapies such as closed-loop (CL) glucose control, also known as artificial pancreas (AP) systems, have shown significant improvement in type 1 diabetes mellitus (T1DM) management. However, demanding patient intervention is still required, particularly at meal times. To reduce treatment burden, the automatic regulation of glucose (ARG) algorithm mitigates postprandial glucose excursions without feedforward insulin boluses. This work assesses feasibility of this new strategy in a clinical trial. Methods: A 36-hour pilot study was performed on five T1DM subjects to validate the ARG algorithm. Subjects wore a subcutaneous continuous glucose monitor (CGM) and an insulin pump. Insulin delivery was solely commanded by the ARG algorithm, without premeal insulin boluses. This was the first clinical trial in Latin America to validate an AP controller. Results: For the total 36-hour period, results were as follows: average time of CGM readings in range 70-250 mg/dl: 88.6%, in range 70-180 mg/dl: 74.7%, <70 mg/dl: 5.8%, and <50 mg/dl: 0.8%. Results improved analyzing the final 15-hour period of this trial. In that case, the time spent in range was 70-250 mg/dl: 94.7%, in range 70-180 mg/dl: 82.6%, <70 mg/dl: 4.1%, and <50 mg/dl: 0.2%. During the last night the time spent in range was 70-250 mg/dl: 95%, in range 70-180 mg/dl: 87.7%, <70 mg/dl: 5.0%, and <50 mg/dl: 0.0%. No severe hypoglycemia occurred. No serious adverse events were reported. Conclusions: The ARG algorithm was successfully validated in a pilot clinical trial, encouraging further tests with a larger number of patients and in outpatient settings."
Automatic glucose control during meals and exercise in type 1 diabetes: proof-of-concept in silico tests using a switched LPV approach
(2021) Colmegna, Patricio; Bianchi, Fernando D.; Sánchez-Peña, Ricardo
"Keeping the blood glucose levels within the safe range during meals and exercise still represents a major hurdle not only for patients with type 1 diabetes (T1D), but also for Artificial Pancreas (AP) systems. One of the reasons a fully (autonomous) closed-loop solution has not been released onto the market yet is the slow action of current insulin analogs. To partially overcome this limitation, the authors have previously designed a switched control strategy equipped with an insulin-on-board (IOB) safety loop that mitigates meal-related glucose excursions without carbohydrate counting. In this paper, a similar strategy based on a Linear Parameter-Varying (LPV) control law has been adapted to safely handle also exercise challenges with minimum user intervention. In silico results using the UVA/Padova simulator evidence that the proposed closedloop scheme is feasible under moderate-intense exercise bouts by effectively and safely reducing the risk of hypoglycemia."
Automatic regulatory control in type 1 diabetes without carbohydrate counting
(2018-05) Colmegna, Patricio; Garelli, Fabricio; De Battista, Hernán; Sánchez-Peña, Ricardo
"A new approach to automatically regulate the glucose level in type 1 diabetes is presented in this work. This is the so-called Automatic Regulation of Glucose (ARG) algorithm, which is based on a switched Linear Quadratic Gaussian (LQG) inner controller, combined with an outer sliding mode safety loop with Insulin on Board (IOB) constraints. In silico and in vivo results without feedforward insulin boluses delivered at meal times indicate that safe blood glucose control can be achieved by the proposed controller. This controller is simple to migrate to well-known hardware platforms, and intuitive to tune using a priori clinical information."
Classification based on dynamic mode decomposition applied to brain recognition of context
(2021-09) Martínez, Sebastián; Silva, Azul; García Violini, Demián; Piriz, Joaquin; Belluscio, Mariano; Sánchez-Peña, Ricardo
"Local Field Potentials (LFPs) are easy to access electrical signals of the brain that represent the summation in the extracellular space, of currents originated within the neurons. As such, LFPs could contain infor mation about ongoing computations in neuronal circuits and could potentially be used to design brain machine interface algorithms. However how brain computations could be decoded from LFPs is not clear. Within this context, a methodology for signal classification is proposed in this study, particularly based on the Dynamic Mode Decomposition method, in conjunction with binary clustering routines based on supervised learning. Note that, although the classification methodology is presented here in the context of a biological problem, it can be applied to a broad range of applications. Then, as a case-study, the proposed method is validated with the classification of LFP-based brain cognitive states. All the analysis, signals, and results shown in this study consider real data measured in the hippocampus, in rats perform ing exploration tasks. Consequently, it is shown that, using the measured LFP, the method infers which context was the animal exploring. Thus, evidence on the spatial codification in LFP signals is consequently provided, which still is an open question in neuroscience."
Complexity reduction of piecewise affine linear parameter varying controllers
(2024-05-03) Bianchi, Fernando D.; Sánchez-Peña, Ricardo S.
This work analyzes the design and implementation of piecewise affine (PWA) Linear Parameter Varying (LPV) controllers. PWA-LPV models can be employed to describe complex nonlinear or time-varying systems with the aim of control design. The complexity of a PWA-LPV controller depends on the number of local models used to describe the plant. Here we propose a methodology to reduce this number and thus simplify the design and implementation complexity of the resulting controller without a significant performance degradation. The methodology is illustrated by an academic example and a more realistic wind turbine control application.
Control no-híbrido de glucemia ensayado en pacientes ambulatorios con Diabetes Tipo 1
(2022-07) Garelli, Fabricio; Fushimi, Emilia; Rosales, Nicolás; Arambarri, Delfina; Serafini, María Cecilia; De Battista, Hernán; Grosembacher, Luis; Sánchez-Peña, Ricardo
"En este trabajo se presenta la experiencia argentina en el problema de regulación de los niveles de glucosa en sangre para pacientes con Diabetes Mellitus Tipo 1 (insulino-dependientes), denominado Páncreas Artificial. El grupo de trabajo ha realizado 3 pruebas clínicas, las primeras en Latinoamérica. Las dos primeras fueron concretadas en 2016 y 2017, ambas en el Hospital Italiano de Buenos Aires (HIBA) con 5 pacientes adultos durante 36 hs. En la segunda de ellas se utilizó un nuevo algoritmo de control de lazo cerrado puro (sin bolo prandial), llamado ARG (Automatic Regulation of Glucose) y basado en un control LQG conmutado en combinación con una capa de seguridad llamada SAFE (Safety Auxiliary Feedback Element). Más recientemente y en plena pandemia de COVID-19 se llevó a cabo la primera prueba ambulatoria, realizada en 2021 en un hotel con 5 pacientes durante 6 días. En esta tercera prueba además, se utilizó una plataforma desarrollada por la Universidad Nacional de La Plata (UNLP), denominada InsuMate. Ésta conecta el celular con la bomba de insulina y el monitor de glucosa, aloja el algoritmo de control y permite el monitoreo remoto de múltiples pacientes. Los resultados obtenidos sugieren que el uso del algoritmo ARG en forma ambulatoria es factible, seguro y eficaz en comparación con la terapia usual. Asimismo, la plataforma InsuMate resultó ser intuitiva y sencilla para los usuarios, tanto médicos como pacientes participantes del ensayo, logrando un tiempo de funcionamiento del lazo cerrado superior al 95 %."
Control-oriented model with intra-patient variations for an artificial pancreas
(2020) Moscoso-Vásquez, Marcela; Colmegna, Patricio; Rosales, Nicolás; Garelli, Fabricio; Sánchez-Peña, Ricardo
"In this work, a low-order model designed for glucose regulation in Type 1 Diabetes Mellitus (T1DM) is obtained from the UVA/Padova metabolic simulator. It captures not only the nonlinear behavior of the glucose-insulin system, but also intrapatient variations related to daily insulin sensitivity (SI) changes. To overcome the large inter-subject variability, the model can also be personalized based on a priori patient information. The structure is amenable for linear parameter varying (LPV) controller design, and represents the dynamics from the subcutaneous insulin input to the subcutaneous glucose output. The eficacy of this model is evaluated in comparison with a previous control-oriented model which in turn is an improvement of previous models. Both models are compared in terms of their open- and closed-loop differences with respect to the UVA/Padova model. The proposed model outperforms previous T1DM control oriented models, which could potentially lead to more robust and reliable controllers for glycemia regulation."
Data-driven fault diagnosis and robust control: application to PEM fuel cell systems
(2018-08) Ocampo-Martínez, Carlos; Sánchez-Peña, Ricardo; Bianchi, Fernando D.; Ingimundarson, Ari
"A data-driven methodology that includes the unfalsified control concept in the framework of fault diagnosis and isolation (FDI) and fault-tolerant control (FTC) is presented. The selection of the appropriate controller from a bank of controllers in a switching supervisory control setting is performed by using an adequate FDI outcome. By combining simultaneous online performance assessment of multiple controllers with the fault diagnosis decision from structured hypothesis tests, a diagnosis statement regarding what controller is most suitable to deal with the current (nominal or faulty) mode of the plant is obtained. Switching strategies that use the diagnosis statement are also proposed. This approach is applied to a nonlinear experimentally validated model of the breathing system of a polymer electrolyte membrane fuel cell. The results show the effectiveness of this FDI–fault-tolerant control data-driven methodology."
Distributed data-driven UAV formation control via evolutionary games: experimental results
(2021-07) Barreiro-Gomez, Julian; Mas, Ignacio; Giribet, Juan I.; Moreno, Patricio; Ocampo-Martínez, Carlos; Sánchez-Peña, Ricardo; Quijano, Nicanor
"This work proposes a novel data-driven distributed formation-control approach based on multi-population evolutionary games, which is structured in a leader-follower scheme. The methodology considers a time-varying communication graph that describes how the multiple agents share information to each other. We present stability guarantees for configurations given by time-varying interaction networks, making the proposed method suitable for real-world problems where communication constraints change along the time. Additionally, the proposed formation controller allows for an agent to leave or enter the group without the need to modify the behaviors of other agents in the group. This game-theoretical approach is evaluated through numerical simulations and real outdoors experimental results using a fleet of aerial autonomous vehicles, showing the control performance."
Dynamic modelling of alkaline self-pressurized electrolyzers: a phenomenological-based semiphysical approach
(2020-09) David, Martín Rafael; Álvarez, Hernán; Ocampo-Martínez, Carlos; Sánchez-Peña, Ricardo
"This paper proposes a phenomenological based semiphysical model (PBSM) for a self-pressurized alkaline electrolyzer. The model, based on mass and energy balances, represents the dynamic behaviour of hydrogen and oxygen production using electrolysis. The model allows to anticipate operational variables as dynamic responses in the concentrations of the electrolytic cell, and variations in both, level and pressure, at the gas separation chambers due to the change in electric current. The model parameters have been adjusted based on experimental measurements taken from an available prototype and through a suitable identification process. Simulation results replicate the current dynamic response of the experimental self-pressurized electrolyzer assembly. This model proves to be useful in the improvement of the control of gas production rate in this kind of assemblies, both as a validated simulation platform and as a source of reduced order models for model-based control design."
Dynamical models in neuroscience from a closed-loop control perspective
(2022-01-28) Martínez, Sebastián; García Violini, Demián; Belluscio, Mariano; Piriz, Joaquin; Sánchez-Peña, Ricardo
"Modifying neural activity is a substantial goal in neuroscience that facilitates the understanding of brain functions and the development of medical therapies. Neurobiological models play an essential role, contributing to the understanding of the underlying brain dynamics. In this context, control systems represent a fundamental tool to provide a correct articulation between model stimulus (system inputs) and outcomes (system outputs). However, throughout the literature there is a lack of discussions on neurobiological models, from the formal control perspective. In general, existing control proposals applied to this family of systems, are developed empirically, without theoretical and rigorous framework. Thus, the existing control solutions, present clear and significant limitations. The focus of this work is to survey dynamical neurobiological models that could serve for closed-loop control schemes or for simulation analysis. Consequently, this paper provides a comprehensive guide to discuss and analyze control oriented neurobiological models. It also provides a potential framework to adequately tackle control problems that could modify the behavior of single neurons or networks. Thus, this study constitutes a key element in the upcoming discussions and studies regarding control methodologies applied to neurobiological systems, to extend the present research and understanding horizon for this field."
First outpatient clinical trial of a full closed-loop artificial pancreas system in South America
(2022-05) Garelli, Fabricio; Fushimi, Emilia; Rosales, Nicolás; Arambarri, Delfina; Mendoza, Leandro; Serafini, María Cecilia; Moscoso-Vásquez, Marcela; Stasi, Marianela; Duette, Patricia; García Arabehety, Julia; Giunta, Javier; De Battista, Hernán; Sánchez-Peña, Ricardo; Grosembacher, Luis
"The first two studies of an artificial pancreas (AP) system carried out in Latin America took place in 2016 (phase 1) and 2017 (phase 2). They evaluated a hybrid algorithm from the University of Virginia (UVA) and the automatic regulation of glucose (ARG) algorithm in an inpatient setting using an AP platform developed by the UVA. The ARG algorithm does not require carbohydrate (CHO) counting and does not deliver meal priming insulin boluses. Here, the first outpatient trial of the ARG algorithm using an own AP platform and doubling the duration of previous phases is presented."
H∞ control experiments for increasing H2 purity in high-pressure alkaline electrolyzers
(2024) David, Martín; Bianchi, Fernando D.; Ocampo-Martínez, Carlos; Sánchez-Peña, Ricardo
In this paper, an H∞ control strategy is implemented in a prototype alkaline electrolyzer to maintain equalized the liquid levels in the separations chambers while following a pressure reference. The aim is to minimize the contamination of the gases produced by the electrolyzer. To this end, two outlet valves are controlled in the output lines of both gases: H2 and O2. The performance of the proposed control strategy was experimentally evaluated under different operating conditions. In all cases, H2 contamination in O2 was below 0.2%.
Industry engagement with control research: perspective and messages
(2020) Samad, Tariq; Bauer, Margret; Bortoff, Scott; Di Cairano, Stefano; Fagiano, Lorenzo; Odgaard, Peter Fogh; Rhinehart, R. Russell; Sánchez-Peña, Ricardo; Serbezov, Atanas; Ankersen, Finn; Goupil, Philippe; Grosman, Benyamin; Heertjes, Marcel; Mareels, Iven; Sosseh, Raye
"Despite the enormous benefit that has accrued to society from control technology and the continuedvitality of control science as a research field, there is broad consensus that the practitioners of control andthe academic research community are insufficiently engaged with each other. We explore this concernwith reference to the oft-cited theory/practice gap but also from an industry perspective. The core ofthis article is comprised of ten “messages,”intended primarily for researchers interested in the practicalimpact of their work, that we hope shed insight on the industry mindset. Results from surveys and otherdata are cited to underpin the points. Some educational synergies between industry and academia arealso noted. To highlight the continuing relevance of control science to industry, several recent examples ofsuccessful, deployed advanced control solutions are presented. The authors of this article are members ofthe IFAC Industry Committee, formally established in 2017 with objectives that include (per the updatedIFAC Constitution) “increasing industry participation in and impact from IFAC activities.”"
Invalidation and low-order model set for artificial pancreas robust control design
(2019) Bianchi, Fernando D.; Moscoso-Vásquez, Marcela; Colmegna, Patricio; Sánchez-Peña, Ricardo
"The purpose of this work is to compute a linear parameter-varying (LPV) model set that describes the insulin-glucose dynamics in type 1 diabetes (T1D). This set includes a nominal LPV model and dynamic uncertainty and is amenable to controller design. The nominal model is an LPV control-oriented model previously published by the authors that is (in)validated in this work against the UVA/Padova metabolic simulator. The result is a set of models that is used to design a switched LPV robust controller to account for nonlinearities and variations in insulin sensitivity (SI). Closed-loop responses obtained with the robust controller and a nominal one are compared. Results illustrate the convenience of including robust strategies in designing control laws for an artificial pancreas (AP). "
Linear parameter-varying model to design control laws for an artificial pancreas
(2018-02) Colmegna, Patricio; Sánchez-Peña, Ricardo; Gondhalekar, Ravi
"The contribution of this work is the generation of a control-oriented model for insulin-glucose dynamic regulation in type1 diabetes mellitus (T1DM). The novelty of this model is that it includes the time-varying nature, and the inter-patient variability of the glucose-control problem. In addition, the model is well suited for well-known and standard controller synthesis procedures. The outcome is an average linear parameter-varying (LPV) model that captures the dynamics from the insulin delivery input to the glucose concentration output constructed based on the UVA/Padova metabolic simulator. Finally, a system-oriented reinterpretation of the classical ad-hoc 1800 rule is applied to adapt the model’s gain."
LPV control of a magnetic bearing experiment
(2010-10) Ghersin, Alejandro S.; Smith, R. S.; Sánchez-Peña, Ricardo
"An LPV (Linear Parameter Varying) controller design example for a Magnetic Bearing System is presented. A linear model of the system including bending modes and imbalance is described. Simulations and experimental results show the usefulness of the LPV method with eigenvalue clustering constraints in spite of the limited rotation rate range. The results show that this method facilitates simulation and allows implementation. Conclusions are drawn on the limited range for the rotation rate the LPV controller allows for."

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