Numerical solution of optimal control problems with constant control delays

We investigate a class of optimal control problems that exhibit constant exogenously given delays in the control in the equation of motion of the differential states. Therefore, we formulate an exemplary optimal control problem with one stock and one control variable and review some analytic properties of an optimal solution. However, analytical considerations are quite limited in case of delayed optimal control problems. In order to overcome these limits, we reformulate the problem and apply direct numerical methods to calculate approximate solutions that give a better understanding of this class of optimization problems. In particular, we present two possibilities to reformulate the delayed optimal control problem into an instantaneous optimal control problem and show how these can be solved numerically with a stateof- the-art direct method by applying Bock’s direct multiple shooting algorithm. We further demonstrate the strength of our approach by two economic examples.

Evaluating the optimal timing of surgical antimicrobial prophylaxis: study protocol for a randomized controlled trial

BACKGROUND Surgical site infections are the most common hospital-acquired infections among surgical patients. The administration of surgical antimicrobial prophylaxis reduces the risk of surgical site infections . The optimal timing of this procedure is still a matter of debate. While most studies suggest that it should be given as close to the incision time as possible, others conclude that this may be too late for optimal prevention of surgical site infections. A large observational study suggests that surgical antimicrobial prophylaxis should be administered 74 to 30 minutes before surgery. The aim of this article is to report the design and protocol of a randomized controlled trial investigating the optimal timing of surgical antimicrobial prophylaxis.Methods/design: In this bi-center randomized controlled trial conducted at two tertiary referral centers in Switzerland, we plan to include 5,000 patients undergoing general, oncologic, vascular and orthopedic trauma procedures. Patients are randomized in a 1:1 ratio into two groups: one receiving surgical antimicrobial prophylaxis in the anesthesia room (75 to 30 minutes before incision) and the other receiving surgical antimicrobial prophylaxis in the operating room (less than 30 minutes before incision). We expect a significantly lower rate of surgical site infections with surgical antimicrobial prophylaxis administered more than 30 minutes before the scheduled incision. The primary outcome is the occurrence of surgical site infections during a 30-day follow-up period (one year with an implant in place). When assuming a 5 surgical site infection risk with administration of surgical antimicrobial prophylaxis in the operating room, the planned sample size has an 80% power to detect a relative risk reduction for surgical site infections of 33% when administering surgical antimicrobial prophylaxis in the anesthesia room (with a two-sided type I error of 5%). We expect the study to be completed within three years. DISCUSSION The results of this randomized controlled trial will have an important impact on current international guidelines for infection control strategies in the hospital. Moreover, the results of this randomized controlled trial are of significant interest for patient safety and healthcare economics.Trial registration: This trial is registered on ClinicalTrials.gov under the identifier NCT01790529.

Ego depletion and persistent performance in a cycling task

We tested the assumption that persistent performance in an exhausting indoor cycling task would depend on momentarily available self-control strength (N = 20 active participants). In a within-subjects design (two points of measurement, exactly seven days apart), participants’ self-control strength was experimentally manipulated (depletion: yes vs. no; order counterbalanced) via the Stroop test before the participants performed a cycling task. In line with our hypothesis, hierarchical linear modelling (HLM) revealed that participants consistently performed worse over a period of 18 minutes when they were ego depleted. In addition, HLM analysis revealed that depleted participants invested less effort in the cycling task, as indicated by their lower heart rate. This effect escalated over time, as indicated by a time × condition interaction. These results indicate that self-control strength is necessary to obtain an optimal level of performance in endurance tasks requiring high levels of persistence. Practical implications are discussed.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.

The Making of Optimal and Consistent Policy: An Analytical Framework for Monetary Models

This paper shows that optimal policy and consistent policy outcomes require the use of control-theory and game-theory solution techniques. While optimal policy and consistent policy often produce different outcomes even in a one-period model, we analyze consistent policy and its outcome in a simple model, finding that the cause of the inconsistency with optimal policy traces to inconsistent targets in the social loss function. As a result, the central bank should adopt a loss function that differs from the social loss function. Carefully designing the central bank s loss function with consistent targets can harmonize optimal and consistent policy. This desirable result emerges from two observations. First, the social loss function reflects a normative process that does not necessarily prove consistent with the structure of the microeconomy. Thus, the social loss function cannot serve as a direct loss function for the central bank. Second, an optimal loss function for the central bank must depend on the structure of that microeconomy. In addition, this paper shows that control theory provides a benchmark for institution design in a game-theoretical framework.

The Making of Optimal and Consistent Policy: An Implementation Theory Framework for Monetary Policy

This paper shows that optimal policy and consistent policy outcomes require the use of control-theory and game-theory solution techniques. While optimal policy and consistent policy often produce different outcomes even in a one-period model, we analyze consistent policy and its outcome in a simple model, finding that the cause of the inconsistency with optimal policy traces to inconsistent targets in the social loss function. As a result, the social loss function cannot serve as a direct loss function for the central bank. Accordingly, we employ implementation theory to design a central bank loss function (mechanism design) with consistent targets, while the social loss function serves as a social welfare criterion. That is, with the correct mechanism design for the central bank loss function, optimal policy and consistent policy become identical. In other words, optimal policy proves implementable (consistent).

Design of long-term animal bioassay for low-dose extrapolation using a multistage model

Conventional designs of animal bioassays allocate the same number of animals into control and dose groups to explore the spontaneous and induced tumor incidence rates, respectively. The purpose of such bioassays are (a) to determine whether or not the substance exhibits carcinogenic properties, and (b) if so, to estimate the human response at relatively low doses. In this study, it has been found that the optimal allocation to the experimental groups which, in some sense, minimize the error of the estimated response for low dose extrapolation is associated with the dose level and tumor risk. The number of dose levels has been investigated at the affordable experimental cost. The pattern of the administered dose, 1 MTD, 1/2 MTD, 1/4 MTD,....., etc. plus control, gives the most reasonable arrangement for the low dose extrapolation purpose. The arrangement of five dose groups may make the highest dose trivial. A four-dose design can circumvent this problem and has also one degree of freedom for testing the goodness-of-fit of the response model.^ An example using the data on liver tumors induced in mice in a lifetime study of feeding dieldrin (Walker et al., 1973) is implemented with the methodology. The results are compared with conclusions drawn from other studies. ^

Rabies control in the developing world: Results of a cross-sectional study in Bohol, Philippines

Rabies remains a significant problem in much of the developed world, where canine rabies is not well controlled, and the bite of an infected dog is the most common means of transmission. The Philippines continues to report several hundred cases of human rabies every year, and many more cases go undetected. In recent years, the province of Bohol has been targeted by the Philippine government and the World Health Organization for a rabies eradication program. ^ The primary objective of this dissertation research was to describe factors associated with dog vaccination coverage and knowledge, attitudes, and practices regarding rabies among households in Bohol, Philippines. Utilizing a cross-sectional cluster survey design, we sampled 460 households and 541 dogs residing within dog-owning households. ^ Multivariate linear regression was used to examine potential associations between knowledge, attitudes, and practices (KAPs) and variables of interest. Forty-six percent of households knew that rabies was spread through the bite of an infected dog. The mean knowledge score was 8.36 (SD: ± 3.4; range: 1–24). We found that having known someone with rabies was significantly associated with an almost one point increase in the knowledge score (β = 0.88; p = 0.02). The mean attitudes score was 5.65 (SD: ± 0.63; range: 2–6), and the mean practices score was 7.07 (SD: ± 1.7; range: 2–9). Both the attitudes score and the practices score were positively and significantly associated with only the knowledge score and no other covariates. ^ Multivariate logistic regression was used to examine associations between dog vaccination coverage and variables of interest. Approximately 71% of owned dogs in Bohol were reported as vaccinated at some time during their lives. We found that a dog's age was significantly associated with vaccination, and the odds of vaccination increased in a linear fashion with age. We also found that dogs had approximately twice the odds of being vaccinated if they were confined both day and night to the household premises or if the owner was employed; however, these results were only marginally significant (p = 0.07) in the multivariate model. ^ Finally, a systematic review was conducted on canine rabies vaccination and dog population demographics in the developing world. We found few studies on this topic, especially in countries where the burden of rabies is greatest. Overall, dog ownership is high. Dogs are quite young and do not live very long due to disease and accidents. The biggest deterrent to vaccination is the rapid dog population turnover. ^ It is our hope that this work will be used to improve dog rabies vaccination programs around the world and save lives, both human and canine.^

Optimal, minimax, and Bayesian two-stage designs in two-dose phase II clinical trials

Background: For most cytotoxic and biologic anti-cancer agents, the response rate of the drug is commonly assumed to be non-decreasing with an increasing dose. However, an increasing dose does not always result in an appreciable increase in the response rate. This may especially be true at high doses for a biologic agent. Therefore, in a phase II trial the investigators may be interested in testing the anti-tumor activity of a drug at more than one (often two) doses, instead of only at the maximum tolerated dose (MTD). This way, when the lower dose appears equally effective, this dose can be recommended for further confirmatory testing in a phase III trial under potential long-term toxicity and cost considerations. A common approach to designing such a phase II trial has been to use an independent (e.g., Simon's two-stage) design at each dose ignoring the prior knowledge about the ordering of the response probabilities at the different doses. However, failure to account for this ordering constraint in estimating the response probabilities may result in an inefficient design. In this dissertation, we developed extensions of Simon's optimal and minimax two-stage designs, including both frequentist and Bayesian methods, for two doses that assume ordered response rates between doses. ^ Methods: Optimal and minimax two-stage designs are proposed for phase II clinical trials in settings where the true response rates at two dose levels are ordered. We borrow strength between doses using isotonic regression and control the joint and/or marginal error probabilities. Bayesian two-stage designs are also proposed under a stochastic ordering constraint. ^ Results: Compared to Simon's designs, when controlling the power and type I error at the same levels, the proposed frequentist and Bayesian designs reduce the maximum and expected sample sizes. Most of the proposed designs also increase the probability of early termination when the true response rates are poor. ^ Conclusion: Proposed frequentist and Bayesian designs are superior to Simon's designs in terms of operating characteristics (expected sample size and probability of early termination, when the response rates are poor) Thus, the proposed designs lead to more cost-efficient and ethical trials, and may consequently improve and expedite the drug discovery process. The proposed designs may be extended to designs of multiple group trials and drug combination trials.^

Estrategias para el control microclimático del espacio entre edificaciones en clima cálido – húmedo

La presente investigación parte del problema en las zonas de clima cálido - húmedo en las cuales se producen impactos asociados a la incomodidad térmica producto de la intensa radiación solar, altas temperaturas y elevada humedad. Estos factores reducen la calidad de los espacios abiertos y desarrollan en la población una actitud de rechazo hacia el uso del microespacio urbano entre edificaciones en los desarrollos urbanos - conjuntos urbanos - , los mismos frecuentemente admiten soluciones que al parecer no contribuyen a la realización de las actividades comunes de esparcimiento de la población residente. Por lo tanto, el objetivo de la investigación es profundizar en la temática urbano - ambiental - social y el diseño urbano vinculada a la particularidad morfológica local, las condiciones microclimáticas, el uso del microespacio y los requerimientos de los usuarios. La finalidad de desarrollar estrategias de control microclimático del microespacio entre edificios en clima cálido - húmedo en búsqueda de soluciones óptimas que satisfagan las necesidades de los usuarios de los espacios exteriores en estas áreas residenciales. La investigación se centra en el estudio de las particularidades contextuales relacionadas con el microclima y las características urbanas - morfotipológicas, básicamente los factores microclimáticos (soleamiento y ventilación), los morfológicos y edificatorios y las características de las superficies (pavimentos). En coherencia con el objetivo propuesto el trabajo se desarrolla en cuatro fases: la primera aborda la revisión documental, literatura relevante e investigaciones relativas a la calidad ambiental, medio social, medio físico, el microespacio urbano, control y diseño sostenible, modelización proyectual y estrategias sostenibles; la segunda fase se refiere al marco contextual, características urbanas, datos climáticos locales, planes y procesos urbanos, tipologías y conformación urbana. En esta fase se describe el proceso de selección, análisis y evaluación urbano - ambiental de los casos de estudio (conjuntos residenciales). En la tercera fase se aborda el marco evaluativo y estudio de casos, consideraciones físicas, climáticas y valoración térmico - ambiental de los conjuntos residenciales seleccionados. En esta fase se aplican Técnicas Estadísticas y de Simulación Computacional y se analizan los resultados obtenidos. Finalmente, la cuarta fase propositiva incluye el establecimiento de Estrategias, Principios y Lineamientos de optimación térmica y se exponen las Conclusiones parciales de la tesis, alcances y perspectivas futuras. Finalmente, los resultados obtenidos en la investigación demuestran que el análisis en las experiencias de la realidad permiten comprobar que las situaciones y alteraciones ambientales sustanciales, los niveles de afectación térmica y las condiciones de confortabilidad e impacto derivan de las características urbanas, los componentes del microespacio y de las condiciones climáticas las cuales afectan el desarrollo de las actividades y el uso efectivo del microespacio entre edificios. El análisis de los factores morfo - climáticos incidentes y el estudio de los efectos de interacción contribuyen al establecimiento de Principios y Lineamientos para la evaluación y diseño sostenible del microespacio entre edificios y el uso correcto de los elementos del clima en estas áreas urbanas destinadas a la actividad social y al esparcimiento de la población residente. ABSTRACT This research starts from the problem of hot - humid climate zones where impacts related to thermal discomfort are produced as a result from the intense solar radiation and high temperatures and humidity. These factors reduce the quality of open spaces and people develop an attitude of rejection towards the use of urban microspace among buildings within urban developments - urban complexes - . Usually, these complexes admit solutions that apparently do not contribute to the achievement of common leisure activities in the resident dwellers. Therefore, the main purpose of this research is to deepen in the urban - environmental - social issue and urban design linked to the local morphological particularity, microclimate conditions, use of microspace and users’ requirements. In order to develop microclimate control strategies of microspace among buildings in hot - humid climate to look for optimal solutions that satisfy users’ needs of outdoors spaces in these residential areas. The research focuses in the study of contextual particularities related to microclimate and urban - morphotypological characteristics. Basically, microclimate (sunlight and ventilation), morphological and building factors as well as road surface characteristics. According to the proposed objective, this research is developed in four phases: the first one considers documentary review, relevant literature and researches related to environmental quality, social environment, physical environment, urban microspace, control and sustainable design, project modelling and sustainable strategies; while the second phase refers to contextual framework, urban characteristics, local climate data, plans and urban processes, typologies and urban structure. In this phase, the process of selection, analysis and urban - environmental evaluation of case studies (residential complexes) is described. The third phase approaches the assessment framework and case studies, physical and climate considerations as well as environmental - thermal evaluation of selected residential complexes. In this phase, statistical techniques and computational simulations are applied. Likewise, results obtained are analysed. Similarly, fourth and proposing phase includes the establishment of strategies, principles and guidelines of thermal optimization and partial conclusions of the thesis, scopes and future perspectives are exposed. Finally, from the results obtained, it is demonstrated that the analysis on reality experiences allow proving that situations and substantial environmental changes, levels of thermal affectations, comfort conditions and impact derive from urban characteristics, microspace components and from climate conditions which affect the development of activities and the effective use of microspace among buildings. The analysis of incidental morpho - climate factors and the study of interaction effects contribute to the establishment of principles and guidelines for the assessment and sustainable design of microspace among buildings as well as the correct use of climate elements in these urban areas oriented to social and leisure activities of resident population.

X-parameters based analytical design of non-linear microwave circuits Application to oscillator design

Resumen El diseño clásico de circuitos de microondas se basa fundamentalmente en el uso de los parámetros s, debido a su capacidad para caracterizar de forma exitosa el comportamiento de cualquier circuito lineal. La relación existente entre los parámetros s con los sistemas de medida actuales y con las herramientas de simulación lineal han facilitado su éxito y su uso extensivo tanto en el diseño como en la caracterización de circuitos y subsistemas de microondas. Sin embargo, a pesar de la gran aceptación de los parámetros s en la comunidad de microondas, el principal inconveniente de esta formulación reside en su limitación para predecir el comportamiento de sistemas no lineales reales. En la actualidad, uno de los principales retos de los diseñadores de microondas es el desarrollo de un contexto análogo que permita integrar tanto el modelado no lineal, como los sistemas de medidas de gran señal y los entornos de simulación no lineal, con el objetivo de extender las capacidades de los parámetros s a regímenes de operación en gran señal y por tanto, obtener una infraestructura que permita tanto la caracterización como el diseño de circuitos no lineales de forma fiable y eficiente. De acuerdo a esta filosofía, en los últimos años se han desarrollado diferentes propuestas como los parámetros X, de Agilent Technologies, o el modelo de Cardiff que tratan de proporcionar esta plataforma común en el ámbito de gran señal. Dentro de este contexto, uno de los objetivos de la presente Tesis es el análisis de la viabilidad del uso de los parámetros X en el diseño y simulación de osciladores para transceptores de microondas. Otro aspecto relevante en el análisis y diseño de circuitos lineales de microondas es la disposición de métodos analíticos sencillos, basados en los parámetros s del transistor, que permitan la obtención directa y rápida de las impedancias de carga y fuente necesarias para cumplir las especificaciones de diseño requeridas en cuanto a ganancia, potencia de salida, eficiencia o adaptación de entrada y salida, así como la determinación analítica de parámetros de diseño clave como el factor de estabilidad o los contornos de ganancia de potencia. Por lo tanto, el desarrollo de una formulación de diseño analítico, basada en los parámetros X y similar a la existente en pequeña señal, permitiría su uso en aplicaciones no lineales y supone un nuevo reto que se va a afrontar en este trabajo. Por tanto, el principal objetivo de la presente Tesis consistiría en la elaboración de una metodología analítica basada en el uso de los parámetros X para el diseño de circuitos no lineales que jugaría un papel similar al que juegan los parámetros s en el diseño de circuitos lineales de microondas. Dichos métodos de diseño analíticos permitirían una mejora significativa en los actuales procedimientos de diseño disponibles en gran señal, así como una reducción considerable en el tiempo de diseño, lo que permitiría la obtención de técnicas mucho más eficientes. Abstract In linear world, classical microwave circuit design relies on the s-parameters due to its capability to successfully characterize the behavior of any linear circuit. Thus the direct use of s-parameters in measurement systems and in linear simulation analysis tools, has facilitated its extensive use and success in the design and characterization of microwave circuits and subsystems. Nevertheless, despite the great success of s-parameters in the microwave community, the main drawback of this formulation is its limitation in the behavior prediction of real non-linear systems. Nowadays, the challenge of microwave designers is the development of an analogue framework that allows to integrate non-linear modeling, large-signal measurement hardware and non-linear simulation environment in order to extend s-parameters capabilities to non-linear regimen and thus, provide the infrastructure for non-linear design and test in a reliable and efficient way. Recently, different attempts with the aim to provide this common platform have been introduced, as the Cardiff approach and the Agilent X-parameters. Hence, this Thesis aims to demonstrate the X-parameter capability to provide this non-linear design and test framework in CAD-based oscillator context. Furthermore, the classical analysis and design of linear microwave transistorbased circuits is based on the development of simple analytical approaches, involving the transistor s-parameters, that are able to quickly provide an analytical solution for the input/output transistor loading conditions as well as analytically determine fundamental parameters as the stability factor, the power gain contours or the input/ output match. Hence, the development of similar analytical design tools that are able to extend s-parameters capabilities in small-signal design to non-linear ap- v plications means a new challenge that is going to be faced in the present work. Therefore, the development of an analytical design framework, based on loadindependent X-parameters, constitutes the core of this Thesis. These analytical nonlinear design approaches would enable to significantly improve current large-signal design processes as well as dramatically decrease the required design time and thus, obtain more efficient approaches.

Current Mode with RMS Voltage and Offset Control Loops for a Single-Phase Aircraft Inverter Suitable for Parallel and 3-Phase Operation Modes

Rms voltage regulation may be an attractive possibility for controlling power inverters. Combined with a Hall Effect sensor for current control, it keeps its parallel operation capability while increasing its noise immunity, which may lead to a reduction of the Total Harmonic Distortion (THD). Besides, as voltage regulation is designed in DC, a simple PI regulator can provide accurate voltage tracking. Nevertheless, this approach does not lack drawbacks. Its narrow voltage bandwidth makes transients last longer and it increases the voltage THD when feeding non-linear loads, such as rectifying stages. On the other hand, the implementation can fall into offset voltage error. Furthermore, the information of the output voltage phase is hidden for the control as well, making the synchronization of a 3-phase setup not trivial. This paper explains the concept, design and implementation of the whole control scheme, in an on board inverter able to run in parallel and within a 3-phase setup. Special attention is paid to solve the problems foreseen at implementation level: a third analog loop accounts for the offset level is added and a digital algorithm guarantees 3-phase voltage synchronization.

Predictor paramétrico de glucosa subcutánea

La diabetes mellitus es una enfermedad que se caracteriza por la nula o insuficiente producción de insulina, o la resistencia del organismo a la misma. La insulina es una hormona que ayuda a que la glucosa (por ejemplo la obtenida a partir de los alimentos ingeridos) llegue a los tejidos periféricos y al sistema nervioso para suministrar energía. Hoy en día la tecnología actual permite abordar el desarrollo del llamado “páncreas endocrino artificial”, que consta de un sensor continuo de glucosa subcutánea, una bomba de infusión subcutánea de insulina y un algoritmo de control en lazo cerrado que calcule la dosis de insulina requerida por el paciente en cada momento, según la medida de glucosa obtenida por el sensor y según unos objetivos. El mayor problema que presentan los sistemas de control en lazo cerrado son los retardos, el sensor de glucosa subcutánea mide la glucosa del líquido intersticial, que representa la que hubo en la sangre un tiempo atrás, por tanto, un cambio en los niveles de glucosa en la sangre, debidos por ejemplo, a una ingesta, tardaría un tiempo en ser detectado por el sensor. Además, una dosis de insulina suministrada al paciente, tarda un tiempo aproximado de 20-30 minutos para la llegar a la sangre. Para evitar trabajar en la medida que sea posible con estos retardos, se intenta predecir cuál será el nivel de glucosa en un futuro próximo, para ello se utilizara un predictor de glucosa subcutánea, con la información disponible de glucosa e insulina. El objetivo del proyecto es diseñar una metodología para estimar el valor futuro de los niveles de glucosa obtenida a partir de un sensor subcutáneo, basada en la identificación recursiva del sistema glucorregulatorio a través de modelos lineales y determinando un horizonte de predicción óptimo de trabajo y analizando la influencia de la insulina en los resultados de la predicción. Se ha implementado un predictor paramétrico basado en un modelo autorregresivo ARX que predice con mejor precisión y con menor RMSE que un predictor ZOH a un horizonte de predicción de treinta minutos. Utilizar información relativa a la insulina no tiene efecto en la predicción. El preprocesado, postprocesado y el tratamiento de la estabilidad tienen un efecto muy beneficioso en la predicción. Diabetes mellitusis a group of metabolic diseases in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin produced. The insulin is a hormone that helps the glucose to reach to outlying tissues and the nervous system to supply energy. Nowadays, the actual technology allows raising the development of the “artificial endocrine pancreas”. It involves a continuous glucose sensor, an insulin bump, and a full closed loop algorithm that calculate the insulin units required by patient at any time, according to the glucose measure obtained by the sensor and any target. The main problem of the full closed loop systems is the delays, the glucose sensor measures the glucose in the interstitial fluid that represents the glucose was in the blood some time ago. Because of this, a change in the glucose in blood would take some time to be detected by the sensor. In addition, insulin units administered by a patient take about 20-30 minutes to reach the blood stream. In order to avoid this effect, it will try to predict the glucose level in the near future. To do that, a subcutaneous glucose predictor is used to predict the future glucose with the information about insulin and glucose. The goal of the proyect is to design a method in order to estimate the future valor of glucose obtained by a subcutaneous sensor. It is based on the recursive identification of the regulatory system through the linear models, determining optimal prediction horizon and analyzing the influence of insuline on the prediction results. A parametric predictor based in ARX autoregressive model predicts with better precision and with lesser RMSE than ZOH predictor in a thirty minutes prediction horizon. Using the relative insulin information has no effect in the prediction. The preprocessing, the postprocessing and the stability treatment have many advantages in the prediction.

PSO and neural networks: Optimal combination to solve non linear complex problems

Swarm colonies reproduce social habits. Working together in a group to reach a predefined goal is a social behaviour occurring in nature. Linear optimization problems have been approached by different techniques based on natural models. In particular, Particles Swarm optimization is a meta-heuristic search technique that has proven to be effective when dealing with complex optimization problems. This paper presents and develops a new method based on different penalties strategies to solve complex problems. It focuses on the training process of the neural networks, the constraints and the election of the parameters to ensure successful results and to avoid the most common obstacles when searching optimal solutions.