Control predictivo económico basado en técnicas avanzadas de optimización

Las estrategias de control predictivo supusieron un revulsivo en la industria de procesos, especialmente en industrias del sector petroquímico, donde gracias a los estudios realizados por la academia en este campo fueron capaces de incrementar enormemente sus beneficios gracias a la buena actuación de dichos controladores. La principal razón del gran éxito de este tipo de controladores fue su capacidad de poder trabajar con restricciones, siendo así la única estrategia de control avanzado que ha tenido éxito en esta cuestión. Sin embargo, a pesar de su buen funcionamiento, son aún numerosas las limítaciones que el diseñador del sistema de control ha de afrontar. Dicha limitaciones vienen dadas entre otros motivos, por la dificultad que se presenta a la hora de llevar a cabo el proceso de optimización involucrado en cualquier estrategia de control predictivo. Existen numerosos motivos que hacen que el el problema de optimización sea difícil de resolver, como pueden ser la no convexidad de la función a optimizar, la presencia de no linealidades en el modelo o en las restricciones, etc...Universidad de Sevilla. Máster Universitario en Ingeniería Electrónica, Robótica y Automátic

Risk-Aware Wasserstein Distributionally Robust Control of Vessels in Natural Waterways

In the realm of maritime transportation, autonomous vessel navigation in natural inland waterways faces persistent challenges due to unpredictable natural factors. Existing scheduling algorithms fall short in handling these uncertainties, compromising both safety and efficiency. Moreover, these algorithms are primarily designed for non-autonomous vessels, leading to labor-intensive operations vulnerable to human error. To address these issues, this study proposes a risk-aware motion control approach for vessels that accounts for the dynamic and uncertain nature of tide islands in a distributionally robust manner. Specifically, a model predictive control method is employed to follow the reference trajectory in the time-space map while incorporating a risk constraint to prevent grounding accidents. To address uncertainties in tide islands, a novel modeling technique represents them as stochastic polytopes. Additionally, potential inaccuracies in waterway depth are addressed through a risk constraint that considers the worst-case uncertainty distribution within a Wasserstein ambiguity set around the empirical distribution. Using sensor data collected in the Guadalquivir River, we empirically demonstrate the performance of the proposed method through simulations on a vessel. As a result, the vessel successfully navigates the waterway while avoiding grounding accidents, even with a limited dataset of observations. This stands in contrast to existing non-robust controllers, highlighting the robustness and practical applicability of the proposed approach

Impact of an Antimicrobial Stewardship Program on the Incidence of Carbapenem Resistant Gram-Negative Bacilli: An Interrupted Time-Series Analysis

This article belongs to the Section Antibiotics Use and Antimicrobial Stewardship.Carbapenem-resistant Gram-negative bacilli (CR-GNB) are a critical public health threat, and carbapenem use contributes to their spread. Antimicrobial stewardship programs (ASPs) have proven successful in reducing antimicrobial use. However, evidence on the impact of carbapenem resistance remains unclear. We evaluated the impact of a multifaceted ASP on carbapenem use and incidence of CR-GNB in a high-endemic hospital. An interrupted time-series analysis was conducted one year before and two years after starting the ASP to assess carbapenem consumption, CR-GNB incidence, death rates of sentinel events, and other variables potentially related to CR-GNB incidence. An intense reduction in carbapenem consumption occurred after starting the intervention and was sustained two years later (relative effect −83.51%; 95% CI −87.23 to −79.79). The incidence density of CR-GNB decreased by −0.915 cases per 1000 occupied bed days (95% CI −1.743 to −0.087). This effect was especially marked in CR-Klebsiella pneumoniae and CR-Escherichia coli, reversing the pre-intervention upward trend and leading to a relative reduction of −91.15% (95% CI −105.53 to −76.76) and −89.93% (95% CI −107.03 to −72.83), respectively, two years after starting the program. Death rates did not change. This ASP contributed to decreasing CR-GNB incidence through a sustained reduction in antibiotic use without increasing mortality rates.This research was funded by the Plan Nacional de I + D+i 2013–2016 and Instituto de Salud Carlos III, Subdirección General de Redes y Centros de Investigación Cooperativa, Ministerio de Ciencia, Innovación y Universidades, Spanish Network for Research in Infectious Diseases (REIPI RD16/0016/0008; RD16/0016/0009) co-financed by European Development Regional Fund ‘A way to achieve Europe’ and Operative program intelligent Growth 2014–2020, which did not participate in the development of the program or the analysis of its results

Role of IP-10 to Predict Clinical Progression and Response to IL-6 Blockade With Sarilumab in Early COVID-19 Pneumonia. A Subanalysis of the SARICOR Clinical Trial

© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact [email protected][Background] The Clinical Trial of Sarilumab in Adults With COVID-19 (SARICOR) showed that patients with coronavirus disease 2019 (COVID-19) pneumonia and increased levels of interleukin (IL)-6 might benefit from blockade of the IL-6 pathway. However, the benefit from this intervention might not be uniform. In this subanalysis, we sought to determine if other immunoactivation markers, besides IL-6, could identify which subgroup of patients benefit most from this intervention.[Methods] The SARICOR trial was a phase II, open-label, multicenter, controlled trial (July 2020–March 2021) in which patients were randomized to receive usual care (UC; control group), UC plus a single dose of sarilumab 200 mg (sarilumab-200 group), or UC plus a single dose of sarilumab 400 mg (sarilumab-400 group). Patients who had baseline serum samples for cytokine determination (IL-8, IL-10, monocyte chemoattractant protein–1, interferon-inducible protein [IP]-10) were included in this secondary analysis. Progression to acute respiratory distress syndrome (ARDS) according to cytokine levels and treatment received was evaluated.[Results] One hundred one (88%) of 115 patients enrolled in the SARICOR trial had serum samples (control group: n = 33; sarilumab-200: n = 33; sarilumab-400: n = 35). Among all evaluated biomarkers, IP-10 showed the strongest association with treatment outcome. Patients with IP-10 ≥2500 pg/mL treated with sarilumab-400 had a lower probability of progression (13%) compared with the control group (58%; hazard ratio, 0.19; 95% CI, 0.04–0.90; P = .04). Conversely, patients with IP-10 40 pg/mL. Importantly, IP-10 value <2500 pg/mL might discriminate those individuals who might not benefit from sarilumab therapy among those with high IL-6 levels.This work was supported by the Consejeria de Salud y Familias, Junta de Andalucia, Spain (COVID-19 Research Program, project code COVID-0013-2020). B.G.G. and J.T.C. are supported by General Sub-Directorate of Networks and Cooperative Research Centers, Ministry of Science and Innovation, Spanish Network for Research in Infectious Diseases (REIPI RD16/0016/0001, RD16/0016/0008)—co-financed by the European Regional Development Fund, “A Way to Achieve Europe, Operational Program Smart Growth 2014–2020.” J.C.G. is supported by SCReN (Spanish Clinical Research Network) funded by the ISCIII-Sub-Directorate General for Research Assessment and Promotion through projects PT17/0017/0032 and PT20/0039. R.L.L., C.D.L.F., J.T.-C., and B.G.-G. are supported by the Center of Biomedical Investigation Network for Infectious Diseases (CIBERINFEC) funded by ISCIII through projects CB21/13/00049 and CB21/13/00012.Peer reviewe

Management of multidrug resistant Gram-negative bacilli infections in solid organ transplant recipients: SET/GESITRA-SEIMC/REIPI recommendations

Solid organ transplant (SOT) recipients are especially at risk of developing infections by multidrug resistant (MDR) Gram-negative bacilli (GNB), as they are frequently exposed to antibiotics and the healthcare setting, and are regulary subject to invasive procedures. Nevertheless, no recommendations concerning prevention and treatment are available. A panel of experts revised the available evidence; this document summarizes their recommendations: (1) it is important to characterize the isolate´s phenotypic and genotypic resistance profile; (2) overall, donor colonization should not constitute a contraindication to transplantation, although active infected kidney and lung grafts should be avoided; (3) recipient colonization is associated with an increased risk of infection, but is not a contraindication to transplantation; (4) different surgical prophylaxis regimens are not recommended for patients colonized with carbapenem-resistant GNB; (5) timely detection of carriers, contact isolation precautions, hand hygiene compliance and antibiotic control policies are important preventive measures; (6) there is not sufficient data to recommend intestinal decolonization; (7) colonized lung transplant recipients could benefit from prophylactic inhaled antibiotics, specially for Pseudomonas aeruginosa; (8) colonized SOT recipients should receive an empirical treatment which includes active antibiotics, and directed therapy should be adjusted according to susceptibility study results and the severity of the infection.J.T.S. holds a research contract from the Fundación para la Formación e Investigación de los Profesionales de la Salud de Extremadura (FundeSalud), Instituto de Salud Carlos III. M.F.R. holds a clinical research contract “Juan Rodés” (JR14/00036) from the Spanish Ministry of Economy and Competitiveness, Instituto de Salud Carlos III

Risk factors for infections caused by carbapenem-resistant Enterobacterales: an international matched case-control-control study (EURECA)

Cases were patients with complicated urinary tract infection (cUTI), complicated intraabdominal (cIAI), pneumonia or bacteraemia from other sources (BSI-OS) due to CRE; control groups were patients with infection caused by carbapenem-susceptible Enterobacterales (CSE), and by non-infected patients, respectively. Matching criteria included type of infection for CSE group, ward and duration of hospital admission. Conditional logistic regression was used to identify risk factors. Findings Overall, 235 CRE case patients, 235 CSE controls and 705 non-infected controls were included. The CRE infections were cUTI (133, 56.7%), pneumonia (44, 18.7%), cIAI and BSI-OS (29, 12.3% each). Carbapenemase genes were found in 228 isolates: OXA-48/like, 112 (47.6%), KPC, 84 (35.7%), and metallo-beta-lactamases, 44 (18.7%); 13 produced two. The risk factors for CRE infection in both type of controls were (adjusted OR for CSE controls; 95% CI; p value) previous colonisation/infection by CRE (6.94; 2.74-15.53; <0.001), urinary catheter (1.78; 1.03-3.07; 0.038) and exposure to broad spectrum antibiotics, as categorical (2.20; 1.25-3.88; 0.006) and time-dependent (1.04 per day; 1.00-1.07; 0.014); chronic renal failure (2.81; 1.40-5.64; 0.004) and admission from home (0.44; 0.23-0.85; 0.014) were significant only for CSE controls. Subgroup analyses provided similar results. Interpretation The main risk factors for CRE infections in hospitals with high incidence included previous coloni-zation, urinary catheter and exposure to broad spectrum antibiotics

Optimal navigation management in natural inland waterways

Today, maritime freight transport is one of the most important factors in the development and growth of world economies in an increasingly interconnected and interdependent world. Within the different scenarios, one of the critical environments whose management is particularly delicate and which today continues to pose different challenges to be solved are natural inland waterways, which are natural logistical navigation channels connected to inland ports. Unlike artificial channels, transportation in natural inland waterways presents formidable challenges due to ever-changing environmental conditions and the unpredictability of different natural phenomena, such as the effect of the tide, in addition to the various operational constraints that arise from environmental, economic and safety issues. This doctoral thesis addresses one of the main challenges in this type of canals, which is the optimal and safe management of navigation within the waterways, all this from a practical approach taking into account the industrial framework in which this work takes place. In the first component of this research, we introduce a methodology aimed at finding optimal navigation plans, which are intended to serve as reference guidelines to which vessel pilots can adhere. These plans are designed with the objective of optimising the waiting and sailing times of vessels, which not only leads to a significant improvement in the efficiency of port and logistics operations, but also has a strong economic impact due to the importance of good channel management on the prestige and positioning of the port. It is important to highlight here the great importance of the effect of the tide, which conditions the time windows in which the channel is available due to the dynamic effect it has on the depth of the channel. To address this issue, a methodology for the search of safe crossing windows is proposed in this work, which guarantees the existence of at least one feasible safe trajectory for each vessel included in the plan. To facilitate the practical implementation of the proposed scheduling methodology, an open-source software tool has been developed. This tool equips navigation planners with a practical solution for optimizing vessel routes by considering real-time data and environmental conditions. The second facet of this thesis tackles the inherent uncertainty associated with inland waterways. Unforeseen incidents, including delays and mechanical failures, can disrupt even the best-laid plans. To counteract these uncertainties, we propose strategies for dynamic rescheduling that allow for real-time optimal adjustments in response to unexpected events. These strategies prioritize safety and aim to minimize the overall impact of the incident. To carry out all this, it is necessary to establish an architecture that allows real-time detection of the incident based on the localization data provided by the vessel, as well as a filter that allows the correct identification of the type of incident that has occurred in order to be able to take the correct action. In the last stage of the present work, we go one step further by looking into the future and propose an autonomous strategy for the control of the vessels, thus making each of the them an autonomous robot capable of navigating the estuary without any human intervention and thus reducing the risk of accidents due to human error, and the need for expert pilots. To this end, the use of distributionally robust control strategies applied to the problem of navigation control in natural inland waterways is presented. The main advantage of this type of methodology is that, unlike conventional robust control strategies that require a perfect identification of the different sources of uncertainty affecting navigation, particularly the effect of the tide, the proposed control strategy is able to improve performance relying only on the knowledge of a very limited set of historical depth data

Energy-efficiency-oriented gradient-based economic predictive control of multiple-chiller cooling systems

Cuenta con otro ed.: IFAC-PapersOnLine Incluida en el vol. 53, Issue 2 Article number: 145388The growing use of air conditioning systems has become one of the main drivers of energy consumption in buildings. Many efforts are being made to develop new designs and control strategies to improve energy efficiency and minimise electricity consumption. In this work, a model for a case study of multiple-chiller-based cooling system is presented, based on surrogate models derived from information provided by manufacturers, and the study of the economic performance index. Then, an economic predictive control strategy will aim to operate the system optimizing the efficiency of the plant. Instead of the classical two-layer economic predictive control structure, where the reference to be tracked by the controller is given by a real-time optimizer, here we consider a single-layer control strategy where the gradients with respect to the manipulated inputs of the economic performance index are included in the cost function of the model predictive controller. The resulting optimization problem to be solved on line is a QP, which considerably eases the optimization problem, while also avoiding discrepancies between layers that could lead to loss of feasibility.Feder (UE) DPI2016-76493-C3-1-R

Learning-based NMPC on SoC platforms for real-time applications using parallel Lipschitz interpolation

One of the main problems associated with advanced control strategies is their implementation on embedded and industrial platforms, especially when the target application requires real-time operation. Frequently, the dynamics of the system are totally or partially unknown, and data-driven methods are needed to learn an approximate model of the plant to control. On many occasions, these learning techniques use non-differentiable functions that cannot be handled by most traditional low-level gradient-based optimization methods. In addition, many data-driven techniques require the online processing of a vast amount of data, which may be exceedingly time-consuming for most real-time applications. To solve these two problems at once, we propose a low-cost solution based on a system on a chip (SoC) platform featuring an embedded microprocessor (MP) and a field programmable gate array (FPGA) to implement nonlinear model predictive control strategies. The model employed to make predictions about the future evolution of the system is learnt by means of a data-driven learning method know as parallel Lipschitz interpolation (LI) and implemented in the FPGA part. On the other hand, the optimization problem associated with the model predictive control strategy is solved by software in the MP using an adapted version of the particle swarm optimization method

Real-time monitoring and optimal vessel rescheduling in natural inland waterways

Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND licenseDespite the efforts made by the port community and the academia to develop Efficient strategies to mitigate the effect of unexpected events on the planning of vessels through natural waterways, most scheduling algorithms developed so far are not against these events unforseen events. These incidents may lead to nonoptimal operation or even to potentially dangerous situations. To tackle this issue, in this paper we propose a real-time monitoring architecture and a series of optimal rescheduling strategies to re-schedule vessels in real time when an unexpected incident is detected. The objective is to reduce the impact of the incident in the overall process while preserving safety. This is done by detecting deviations from the originally scheduled plans and taking the proper measures when incidents are detected, which will depend on the type of anomaly detected. The proposed methodology is applied to the case of the Guadalquivir river, a natural waterway located in the south of Spain