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185 p., The main objective of this thesis is to control the electrical three-phase AC machines, using advanced control methods to meet the performance requirements for the plant model. Throughout this thesis, four different electrical three-phase AC machines were employed as motors or generators: the Squirrel Cage Induction Machine (SCIM), Doubly Fed Induction Machine (DFIM), Permanent Magnet Synchronous Machine (PMSM), and Permanent Magnet Vernier Machine (PMVM). When these machines are working as motors or generators, their shaft is mechanically connected to a load. In the generator regimen, two different turbine types were considered: the Wells turbine in Oscillating Water Column (OWC) and Wind Turbine System (WTS).In this thesis, different control techniques are proposed to govern different aspects of the machine. The Integral Sliding Mode Control (ISMC) and Finite Control Set-Model Predictive Control (FCS-MPC) are employed for the current regulation of electrical machines. For velocity regulation, various methods such as the ISMC method, Generalized Predictive Control (GPC) technique, and a GPC-based Proportional Integral (PI) approach were proposed. Three different GPC schemes were implemented: nonlinear, analytical, and industrial, each offering different features.

Los capítulos 5 y 6 están sujetos a confidencialidad por la autora. 158 p., La motivación de esta tesis es ayudar a las empresas manufactureras a adoptar tecnologías de la Industria 4.0 mediante el desarrollo de una solución rentable y confiable para mejorar su rendimiento. El enfoque se centra en el mantenimiento predictivo, que tiene como objetivo reducir los tiempos de inactividad de las máquinas y predecir fallos que provocan averías, aumentando así la productividad y las ganancias. La tesis propone una metodología integral, innovadora y novedosa para la predicción de fallos en el contexto de la Industria 4.0. La metodología consta de dos tareas principales: 1) etiquetado automático de bases de datos parcialmente etiquetadas y 2) obtención del mejor conjunto de parámetros que son predictores de un fallo.La primera tarea se logra mediante un sistema autónomo y fácil de usar llamado PLASH que evalúa y optimiza las diferentes soluciones de agrupamiento realizadas por una nueva métrica semi-supervisada llamada PSOM. La metodología proporciona al usuario tanto los resultados de una manera comprensible como una métrica de confiabilidad. Los resultados experimentales demuestran que PLAHS puede adaptarse, evaluar y proporcionar la mejor solución de etiquetado en diferentes tipos de datos y escenarios, incluido un estudio de caso real de una prensa de estampado en frío para la fabricación de pernos.La segunda tarea se logra mediante una metodología inspirada en la hiper-heurística llamada HIMAFP, que identifica de manera autónoma los parámetros significativos de las series temporales que caracterizan el comportamiento de las variables de proceso relevantes que permiten predecir fallos. La metodología encuentra el conjunto óptimo de parámetros que son predictores de un tipo específico de fallo, proporcionando al usuario final información para detectar la anomalía y anticipar el fallo. Los resultados experimentales demuestran que HIMAFP es efectivo al proporcionar a los expertos en el campo valiosos conocimientos sobre el comportamiento de las var

Los capítulos 5,6 y 7 están sujetos a confidencialidad por el autor. 102 p., La electrónica de potencia está presente en nuestras vidas en la mayoría de nuestras acciones. Toda esta electrónica está basada en los semiconductores de Silicio, tecnología muy madura en la actualidad,sin embargo la aparición de los semiconductores de banda ancha prohibida está proporcionando un importante salto tecnológico frente a los semiconductores de silicio convencionales, ya que gracias a sus características permiten operar por encima de los límites conocidos por el Silicio, tanto en frecuencia de conmutación, en tensiones de bloqueo, como en temperatura máxima de unión, posibilitando optimizarlos diseños de electrónica de potencia, no antes sin superar los retos que presenta su implementación.Para ello, por un lado y debido a sus características diferentes, es necesario desarrollar nuevos controladores de puerta capaces de manejarlos a las altas velocidades de conmutación que soportan, y por otro lado, para exprimir todas todas sus ventajas se deben diseñar nuevos componentes magnéticos reducidos que trabajen a altas frecuencias optimizando y adecuando el sistemas de refrigeración, con el fin de aumentar la densidad de potencia de los nuevos convertidores.Entre los semiconductores de banda ancha prohibida, el Carburo de Silicio y el Nitruro de Galio son los más prometedores. En este trabajo, se muestra la integración del Carburo de silicio en la aplicación detracción ferroviaria y en la aplicación fotovoltaica, y las ventajas que proporcionan frente a un convertidor de las mismas características basado en Silicio convencional.

In this article, we propose an instantaneous complex power control (ICPC) for a grid-tied voltage-source converter, which has two important features: it allows injecting currents with low distortion to the grid, and it allows to significantly reduce the value of the dc link capacitor, which can potentially increase the reliability of the system and decrease its cost (considering different capacitor technologies). The proposal is based on finding the exact active power reference that the controller requires to keep the mean value of the energy in the dc link constant at all times. This means that, even when the loading conditions change, the mean value of the dc link voltage remains unchanged, allowing the reduction of the value of dc link capacitor. The proposed control scheme is validated both through simulations and experimental results.

255 p., The need for rehabilitation has increased over the years. The individualisation of rehabilitation plays an important role in improving the lives of people in need. Within this individualisation of rehabilitation, the use of physical activity data can be very useful to know the condition of the person. But the knowledge of constant physical activity is almost impossible for therapists.The use of technology, with the purpose of helping to know the physical activity performed by people, is becoming more and more common. Through the sensorization of the person, very interesting data can be obtained to help in rehabilitation. In addition, thanks to this sensorization, it is possible to know other types of events, such as a fall, whose rapid action can avoid increasing the need for rehabilitation.Typically this type of sensorization is done using wearable sensors, but several researchers have proposed the use of sensors integrated into assistive devices for walking for those who need them, as this solution is less invasive. While many of the devices can measure physical activity, they have the disadvantage that the sensing elements are fixed to the assistive devices for walking. This may prevent the user from being comfortable, as it is not the assistive device for walking that he/she normally uses. For this reason, the design of an interchangeable sensor tip between different assistive devices for walking is very important.This paper presents an innovative prototype of a sensorized tip that can be interchanged between different assistive devices for walking. It is capable of classifying different physical activities as well as detecting falls. The developed tip is able to adapt to different assistive devices for walking on the market. In addition, this sensorized tip consists of a series of sensors that provide the information needed to classify physical activities and detect falls. These sensors are: a force sensor to measure axial forces; a 3-axis accelerometer, a 3-ax, Errehabilitazio beharra areagotu egin da urteak igaro ahala. Indibidualizazioak oso eginkizun garrantzitsua du errehabilitazio beharra duten pertsonen bizitza hobetzeko. Errehabilitazioaren indibidualizazio horren barruan, jarduera fisikoari buruzko datuak erabiltzea oso baliagarria izan daiteke pertsonaren egoera ezagutzeko. Baina jarduera fisiko etengabea ezagutzea ia ezinezkoa da terapeutentzat.Teknologiaren erabilera, pertsonek egiten duten jarduera fisikoa ezagutzeko, gero eta ohikoagoa da. Pertsonaren sentsorizazioaren bidez, oso datu interesgarriak lor daitezke errehabilitazioan laguntzeko. Gainera, sentsorizazio horri esker, beste gertaera mota batzuk ezagutzea lor daiteke, hala nola erorketa bat gertatzen denean, eta horien jarduera azkarrak errehabilitazio beharra areagotzea ekidin dezake.Oro har, sentsorizazio mota hori sentsore eramangarrien bidez egiten da, baina hainbat ikertzailek proposatu dute sentsore integratuak erabiltzea laguntza teknikoko gailuetan, behar duten pertsonentzat, eta soluzio hori ez da hain inbaditzailea. Gailu askok jarduera fisikoa neur badezakete ere, elementu sentsoreak ibiltzeko laguntza gailuetan finko egotearen eragozpena dute. Horrek erabiltzailea eroso egotea eragotz dezake, ez baita normalean erabiltzen duen ibiltzeko laguntza gailua. Hori dela eta, ibiltzeko laguntza gailu ezberdinen artean alda daitekeen punta sentsorizatu baten diseinua oso garrantzitsua da.Lan honek ibiltzeko laguntza gailu ezberdinen artean trukatzeko gai den punta sentsorizatuaren prototipo berritzailea aurkezten du. Jarduera fisikoak sailkatzeko eta erorikoak detektatzeko gai da. Garatutako punta merkatuko ibiltzeko laguntza gailuetara egokitzeko gai da. Gainera, sentsorizatutako punta honek sentsoreak ditu, jarduera fisikoen sailkapena egiteko eta erorikoak detektatzeko informazioa ematen dutenak. Sentsore hauek dira: indar axialak neurtzeko indar-sentsore bat; 3 ardatzeko azelerometro bat, 3 ardatzeko giroskopio bat eta 3 ardatzeko magnetometro b

The recent literature on event-triggered control has demonstrated the potential of dynamic periodic event-triggered control. Compared to continuous-time event-triggering rules, the benefit of considering periodic event-triggered control is to avoid the Zeno phenomenon, which refers to the situation when there are an infinite number of updates in a bounded interval of time. The idea of periodic event-triggered control is to trigger the control law only at known allowable periodic sampling instants. In this paper, our objective is to relax the constraint on the periodicity of the allowable sampling instants and to adapt this framework to the dynamic event-triggered control, which has not been considered in the literature, as far as we are aware of. Following the successful efforts to assess the stability of aperiodic sampled-data control, here we propose a generic framework to emulate aperiodic dynamic event-triggered control law for linear systems, for which the allowable sampling instants are not necessarily equidistant. Such an analysis is made possible thanks to the looped-functionals framework, which gives the flexibility to consider the periodic/aperiodic static/dynamic event-triggered control in a single formulation. Finally, the efficiency of the proposed results is illustrated through the study of two academic examples.

This work is dedicated to the stability analysis of time-delay systems with a single constant delay using the Lyapunov-Krasovskii theorem. This approach has been widely used in the literature and numerous sufficient conditions of stability have been proposed and expressed as linear matrix inequalities (LMI). The main criticism of the method that is often pointed out is that these LMI conditions are only sufficient, and there is a lack of information regarding the reduction of the conservatism. Recently, scalable methods have been investigated using Bessel-Legendre inequality or orthogonal polynomial-based inequalities. The interest of these methods relies on their hierarchical structure with a guarantee of reduction of the level of conservatism. However, the convergence is still an open question that will be answered for the first time in this paper. The objective is to prove that the stability of a time-delay system implies the feasibility of these scalable LMI, at a sufficiently large order of the Legendre polynomials. Moreover, the proposed contribution is even able to provide an analytic estimation of this order, giving rise to a necessary and sufficient LMI for the stability of time-delay systems.

In safety-critical applications that rely on the solution of an optimization problem, the certification of the optimization algorithm is of vital importance. Certification and suboptimality results are available for a wide range of optimization algorithms. However, a typical underlying assumption is that the operations performed by the algorithm are exact, i.e., that there is no numerical error during the mathematical operations, which is hardly a valid assumption in a real hardware implementation. This is particularly true in the case of fixed-point hardware, where computational inaccuracies are not uncommon. This article presents a certification procedure for the proximal gradient method for box-constrained QP problems implemented in fixed-point arithmetic. The procedure provides a method to select the minimal fractional precision required to obtain a certain suboptimality bound, indicating the maximum number of iterations of the optimization method required to obtain it. The procedure makes use of formal verification methods to provide arbitrarily tight bounds on the suboptimality guarantee. We apply the proposed certification procedure on the implementation of a non-trivial model predictive controller on 32-bit fixed-point hardware.

En este vídeo, el alumno podrá aprender con un ejemplo sencillo cómo realizar la detección de flancos de subida y bajada utilizando bloques FC y lenguaje SCL.

En este video el alumno podrá aprender cómo configurar ejes externos en RobotStudio2023 a través de un ejemplo sencillo de aplicación.

En este vídeo, el alumno podrá aprender con unos ejemplos sencillos la sintaxis de programación en lenguaje RAPID de los condicionales IF, ELSE IF y ELSE.

En este vídeo, el alumno podrá aprender con un ejemplo sencillo cómo programar bloques delay con SCL y haciendo uso de los FC.

En este vídeo, el alumno podrá aprender a configurar tarjetas de red en controladores ABB y definir señales de entrada/salida digitales.

En este vídeo, el alumno podrá aprender con un ejemplo sencillo cómo programar bloques FC para tratamiento simultáneo de señales analógicas con lenguaje SCL.

In developed countries, air conditioning systems have become major contributors to energy consumption in buildings. Cooling installations made up of independent chiller units connected in parallel pose a challenge in f inding the most energy-efficient management strategy. This article proposes a novel economic model predictive control strategy to optimize the operation of multiple-chiller HVAC systems according to an economic cost comprising energy consumption as well as a thermal comfort index. Provided that the gradient of the economic cost function can be calculated or estimated, the proposed controller only entails the solution of a single quadratic programming (QP) problem at each sampling period, reducing computational requirements and thus facilitating the deployment on commercial embedded HVAC management platforms. The proposed controller improves economic performance. As our numerical analysis shows, optimal sequencing is achieved for the case of dualchiller plants. Moreover, the controller adapts to possible variations in the economic criteria, enabling the system to respond to changes in electricity price and user preferences. A realistic case study, using a high fidelity model of a building simulated in TRNSYS, demonstrates the effectiveness of the proposed methodology. In particular, the proposed controller demonstrates to be more efficient than state-of-the-art QP-based economic predictive controllers in achieving a reduction of the energy consumption up to 5.19%, which is in line with the targeted reduction of 7.9% by 2030 in the EU Green Deal’s ‘Fit for 55’ package.

This paper introduces a novel approach for regulating the pose of a free-flying dual-arm anthropomorphic space manipulator system (SMS) using a finite-time state-dependent Riccati equation (SDRE) controller. The proposed system finds applications in on-orbit satellite inspection, servicing, space structure assembly, and debris manipulation. The dual-arm SMS presented in this work consists of two 7 degrees of freedom (DoF) robotic arms mounted on a free-flying spacecraft, resulting in a complex 20-DoF system. Due to the high number of DoFs, advanced controller design and efficient computations are necessary. The finite-time SDRE controller relies on the state-dependent coefficient (SDC) parameterization matrices, which are nonlinear apparent linearizations of the dynamics. Conventionally, the computation of SDC matrices is offline and relies on the a priori derivation of the analytical equations governing the dynamics of the system. However, this strategy becomes computationally impractical for high DoF plants. To overcome this issue and deliver a more viable solution, a numerical method to construct and update the SDC matrices at each time step is presented. This approach relies on a screw-theory-based recursive Newton–Euler algorithm designed to reconstruct the manipulator inertia and Coriolis matrices. These quantities are the building blocks of the SDC parameters used in the synthesis of the SDRE controller. Simulation results demonstrate the performances of the finite-time SDRE controller augmented with the online update of the state-dependent coefficients.

This paper proposes rigid-body modelling and identification procedures for long-reach dual-arm manipulators in a cable-suspended pendulum configuration. The proposed model relies on a virtually constrained open kinematic chain and lends itself to be simulated through the most commonly used robotic simulators without explicitly account for the cables constraints and flexibility. Moreover, a dynamic parameters identification procedure is devised to improve the simulation model fidelity and reduce the sim-to-real gap for controllers deployment. We show the capability of our model to handle different cable configurations and suspension mechanisms by customising it for two representative cable-suspended dual-arm manipulation systems: the LiCAS arms suspended by a drone and the CRANEbot system, featuring two Pilz arms suspended by a crane. The identified dynamic models are validated by comparing their evolution with data acquired from the real systems showing a high (between 91.3% to 99.4%) correlation of the response signals. In a comparison performed with baseline pendulum models, our model increases the simulation accuracy from 64.4% to 85.9%. The simulation environment and the related controllers are released as open-source code.

These days, the implementation of sustainable power generation has led to a difference in propensity in the energy creation and capacity frameworks, compelling them to conquer the hardships that it addresses. Considering the entirety among the suggested technologies, vanadium redox flow batteries (VRFB) stand out as a wonderful choice regarding cyclability and versatility. The point of this study is to break down electrochemical performance of a vanadium redox flow battery cell in two dimensions. To accomplish this, a two- dimensional model comprising an ion exchange membrane, electrode and flow channel was created. A set of electrode compression and flow rates was tested to envision the impact on the velocity field, species concentration and potential and current distributions. As a result of compression, velocity profiles and reaction rates are both increased, by 12.7% and 9.2%, respectively, when applying 50% compression. Higher reaction rates and more stable concentra- tion gradients were induced by higher electrolyte rates. Additionally, over- potential was reduced by 1.5% with the lowest flow rate.

Angle measurement is widely used in the servo positioning and speed control of electrical drives, where optical encoders are employed as sensors and coupled to microcontrollers with complex peripherals to provide effective position and speed measurement methods. These methods can achieve high precision and fast response, but are not particularly efficient with computer resources and require high computational costs. Therefore, fast timers, encoder signal oversampling, and a complex post-processing algorithm are used together in a recent research work to achieve a high-precision speed estimation method. Our work will prove that encoder outputs share the oversampling and noise shaping properties typical of sigma-delta modulated signals if they are sampled regularly. Based on this, a new simple and accurate speed estimation method is proposed. Here, encoder outputs are synchronously sampled, differenced, and low-pass filtered. As a result, the speed estimation circuit and its interface with the control unit are greatly simplified, while high accuracy can be achieved. A detailed mathematical analysis of the proposed technique is also performed, and the results obtained are validated by means of a simulation environment using Matlab and Simulink.

This work investigates the dynamics modeling, control, and impact resolution between a floating object and a free-floating space manipulator (FFSM). The controller design is carried out by using an output- and state-dependent Riccati equation (OSDRE) approach. In a collision between an object and a mechanism, the computation of the generalized velocities and the impact force or impulse, which are interrelated, is a challenging problem. Taking into account the free-floating conditions of the space environment, the conservation of linear and angular momentum equations, combined with the conservation of kinetic energy under the elastic impact assumption, are used to find the unknown variables of the impact problem. The control problem addressed for the FFSM is to regulate its end-effector in a point-to-point motion scenario, this while the space manipulator suffers an unintended impact with a floating object, such as a damaged satellite or space debris. By proposing a safety pause starting with the occurrence of impact and for a short duration thereafter, the proposed OSDRE design succeeds in achieving the end-effector regulation control. Although the FFSM can reach the target point, it is shown that maintaining the end-effector regulation at the target is not feasible due to the momentum imparted to the FFSM as a result of the collision. To this end, we employ a simple thruster control on the space manipulator base to complete the regulation task. The theoretical development and controller design are demonstrated through a simulation case study of a spacecraft equipped with a three-link manipulator colliding with an object.

Distributed electric drive vehicles offer maneuver-ability but face stability challenges under different driving conditions. Model Predictive Control (MPC) algorithms can improve lateral stability, but their high computational demands hinder real-time implementation. To address this, the proposed strategy combines Nonlinear Autoregressive Exogenous (NARX) neural networks with MPC in two ways, namely, Nonlinear Prediction-Nonlinear Optimization (NMPC-NO) and Nonlinear Prediction-Linearization (MPC-NPL). While NMPC-NO involves online nonlinear optimization, MPC-NPL uses local linearization, reducing both the computational load significantly to about 40% of the computation time of MPC and 0.05% of that of nonlinear model predictive control (NMPC). The neural networks are trained and validated on 20 different datasets, with alternative training methods investigated. MATLAB/Simulink simulations under various standardized tests demonstrate the effectiveness of the proposed techniques, highlighting improved handling performance, reduced computation time, and real-time deployment capabilities.

Los capítulos 4 y 5 están sujetos a confidencialidad por el autor. 100 p., Como hipótesis inicial de trabajo de esta tesis se identificó la posibilidad de estimar el estado de salud y capacidad de una batería de plomo estanco de alta temperatura en aplicaciones estacionarias para servicios de respaldo, con nuevos modelos operados en tiempo real y basados en identificación de correlación entre la espectroscopia de la impedancia, y las diferentes condiciones de operación a lo largo de la vida de una batería, así como sus modos de fallo.

Background: The declaration of the COVID-19 pandemic triggered global efforts to control and manage the virus impact. Scientists and researchers have been strongly involved in developing effective strategies that can help policy makers and healthcare systems both to monitor the spread and to mitigate the impact of the COVID-19 pandemic. Machine Learning (ML) and Artificial Intelligence (AI) have been applied in several fronts of the fight. Foremost is diagnostic assistance, encompassing patient triage, prediction of ICU admission and mortality, identification of mortality risk factors, and discovering treatment drugs and vaccines. Objective: This systematic review aims to identify original research studies involving actual patient data to construct ML- and AI-based models for clinical decision support for early response during the pandemic years. Methods: Following the PRISMA methodology, two large academic research publication indexing databases were searched to investigate the use of ML-based technologies and their applications in healthcare to combat the COVID-19 pandemic. Results: The literature search returned more than 1000 papers; 220 were selected according to specific criteria. The selected studies illustrate the usefulness of ML with respect to supporting healthcare professionals for (1) triage of patients depending on disease severity, (2) predicting admission to hospital or Intensive Care Units (ICUs), (3) search for new or repurposed treatments and (4) the identification of mortality risk factors. Conclusion: The ML/AI research community was able to propose and develop a wide variety of solutions for predicting mortality, hospitalizations and treatment recommendations for patients with COVID-19 diagnostic, opening the door for further integration of ML in clinical practices fighting this and forecoming pandemics. However, the translation to the clinical practice is impeded by the heterogeneity of both the datasets and the methodological and computationa

Payload transportation and manipulation by rotorcraft drones are receiving a lot of attention from the military, industrial and logistics research areas. The interactions between the UAV and the payload, plus the means of object attachment or manipulation (such as cables or anthropomorphic robotic arms), may be nonlinear, introducing difficulties in the overall system performance. In this paper, we focus on the current state of the art of aerial transportation systems with suspended loads by a single UAV and a team of them and present a review of different dynamic cable models and control systems. We cover the last sixteen years of the existing literature, and we add a discussion for evaluating the main trends in the referenced research works.

In recent times, there have been notable advancements in solar energy and other renewable sources, underscoring their vital contribution to environmental conservation. Solar cells play a crucial role in converting sunlight into electricity, providing a sustainable energy alternative. Despite their significance, effectively optimizing photovoltaic system parameters remains a challenge. To tackle this issue, this study introduces a new optimization approach based on the coati optimization algorithm (COA), which integrates opposition-based learning and chaos theory. Unlike existing methods, the COA aims to maximize power output by integrating solar system parameters efficiently. This strategy represents a significant improvement over traditional algorithms, as evidenced by experimental findings demonstrating improved parameter setting accuracy and a substantial increase in the Friedman rating. As global energy demand continues to rise due to industrial expansion and population growth, the importance of sustainable energy sources becomes increasingly evident. Solar energy, characterized by its renewable nature, presents a promising solution to combat environmental pollution and lessen dependence on fossil fuels. This research emphasizes the critical role of COA-based optimization in advancing solar energy utilization and underscores the necessity for ongoing development in this field.

Esta Tesis Doctoral aborda el diseño, desarrollo y validación experimental de diferentes métodos para reforzar la percepción de los robots aéreos en escenarios de Inspección y Mantenimiento de infraestructuras industriales y civiles. Los métodos desarrollados permiten la operación totalmente autónoma de los robots aéreos sin depender de ninguna infraestructura externa, asumiendo que todos los sensores, métodos de percepción y dispositivos de procesamiento se encuentran a bordo del robot, y no requieren ninguna alteración del entorno. A lo largo de la Tesis se han seguido tres enfoques principales para el diseño de los diferentes métodos. Primero, el uso de esquemas multisensor que aprovechan las sinergias entre sensores para mitigar las debilidades de cada dispositivo individual. Segundo, la selección del modelo más adecuado para representar y estimar el estado del robot en cada escenario. Tercero, el uso de técnicas de percepción activa que mejoren la calidad de las entradas de percepción. Los enfoques propuestos aportan soluciones complementarias, que han dado lugar al desarrollo de cinco métodos contenidos en esta tesis, diseñados en función de las necesidades de cada aplicación estudiada. En primer lugar, esta Tesis Doctoral presenta un método de localización robusta basado en un enfoque multisensor y multihipótesis, que permite la navegación segura y autónoma de robots aéreos sin GNSS en escenarios complejos de inspección industrial y civil. El método integra características de cámara RGB y LiDAR en el mismo marco estadístico, y adopta un enfoque iterativo multihipótesis eficiente. En segundo lugar, esta Tesis Doctoral introduce el uso de mallas (meshes) probabilísticas para representar superficies localmente planares en misiones de inspección de largo alcance en escenarios pobres en información geométrica. Las mallas permiten representar de forma coherente las superficies planas y usar técnicas de decimación para mejorar la fidelidad del mapa, reduciendo la in, This PhD Thesis addresses the design, development, and experimental validation of different methods for strengthening the perception of aerial robots in the Inspection and Maintenance of industrial and civil infrastructures. The developed perception methods enable fully autonomous aerial robot operation without depending on any external infrastructure, assuming that all involved sensors, perception methods, or processing computers are onboard the aerial robot, and require no alteration of the setting. This PhD Thesis follows three main approaches for the design of these methods. First, the use of multisensor systems that take advantage of complementary sensor information to mitigate the weaknesses of each individual device. Second, the selection of the most adequate state representation and estimation scheme for each studied scenario. Third, the adoption of active perception techniques that improve the quality of the perception inputs. The proposed approaches provide complementary solutions, that have been combined along five different methods during this PhD Thesis, designed in function on the needs of each studied application. First, this PhD Thesis presents a robust multi-sensor multi-hypothesis robot localization method, that allows the safe and autonomous navigation of aerial robots in complex, GNSS-denied industrial and civil inspection scenarios. The method integrates RGB camera and LiDAR features are in the same statistical framework, and adopts an efficient multi-hypothesis iterative scheme to cope with the potentially strong symmetries in the scenarios. Second, this PhD Thesis introduces the use of probabilistic meshes to represent locally planar surfaces in LiDAR-based long-range inspection missions in scenarios that are poor in geometrical information. Meshes consistently represent planar surfaces and enable the use of decimation techniques to reduce the influence of the measurement noise in the map and improve its fidelity. They are combined with a prob

En el ámbito de la tecnología aeroespacial contemporánea, los Vehículos Aéreos No Tripulados (UAVs), comúnmente conocidos como drones, han desempeñado un papel revolucionario en la exploración de espacios aéreos. Entre los diversos tipos de UAVs, los Quad-Rotor, que funcionan con cuatro rotores, han destacado debido a su agilidad en entornos tridimensionales. Esta tesis, titulada "Contribuciones a la Interconexión de Sistemas a través de Red y Control Robusto," se centra en mejorar el control y la estabilidad de estos sistemas. La tesis se divide en dos áreas clave: el diseño de módulos para la interconexión de sistemas de control remoto y sistemas lineales, y el desarrollo de estrategias de control robusto basadas en modelos (linealización por realimentación más modos deslizantes), específicamente para sistemas subactuados. Además, se investiga la viabilidad de utilizar redes de comunicación diversas, como 3G y Wi-Fi, para mejorar la conectividad y el control remoto de UAVs. Para respaldar la investigación, se construyó una plataforma experimental dedicada a Quad-Rotor, que se utilizó para validar las estrategias de control propuestas. En resumen, esta tesis representa un avance significativo en el campo del control de UAVs, abordando cuestiones de interconexión y control robusto en entornos desafiantes de comunicación asíncrona y retrasos.

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 fo

This paper introduces a new decentralized control strategy for an unmanned aerial manipulator (UAM) constrained to the vertical plane. The control strategy comprises two loops: the first compensates for the aerial vehicle’s impact on the manipulator; and the second one implements independent controllers for the aerial vehicle and the manipulator. The controller for the aerial vehicle includes an estimator to compensate for the dynamic influence of the manipulator, even if it is affected by external wind-gust disturbances. The manipulator has two revolute joints; however, it is modeled as an dynamically equivalent manipulator, with one revolute and one prismatic joint. The proposed control strategy’s performance is evaluated using a simulator that includes the vehicle’s aerodynamics and the manipulator’s contact force and moment.

Nowadays, Twitter is one of the most popular social networking services. People post messages called “tweets”, which may contain photos, videos, links and text. With the vast amount of interaction on Twitter, due to its popularity, analyzing Twitter data is of increasing importance. Tweets related to finance can be important indicators for decision makers if analyzed and interpreted in relation to stock market. Financial tweets containing keywords from the BIST100 index were collected and the tweets were tagged as “POSITIVE”, “NEGATIVE” and “NEUTRAL”. Binary and multi-class datasets were created. Word embedding and pre-trained word embedding were used for tweet representation. As classifiers, Neural Network, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU) and GRU-CNN models were used in this study. The best results for binary and multi-class datasets were observed with pre-trained word embedding with the CNN model (83.02%, 72.73%). When word embedding was employed, the Neural Network model had the best results on the multi-class dataset (63.85%) and GRU-CNN had the best results on the binary dataset (80.56%).

The number of people who need to use wheelchair for proper mobility is increasing. The integration of technology into these devices enables the simultaneous and objective assessment of posture, while also facilitating the concurrent monitoring of the functional status of wheelchair users. In this way, both the health personnel and the user can be provided with relevant information for the recovery process. This information can be used to carry out an early adaptation of the rehabilitation of patients, thus allowing to prevent further musculoskeletal problems, as well as risk situations such as ulcers or falls. Thus, a higher quality of life is promoted in affected individuals. As a result, this paper presents an orderly and organized analysis of the existing postural diagnosis systems for detecting sitting anomalies in the literature. This analysis can be divided into two parts that compose such postural diagnosis: on the one hand, the monitoring devices necessary for the collection of postural data and, on the other hand, the techniques used for anomaly detection. These anomaly detection techniques will be explained under two different approaches: the traditional generalized approach followed to date by most works, where anomalies are treated as incorrect postures, and a new individualized approach treating anomalies as changes with respect to the normal sitting pattern. In this way, the advantages, limitations and opportunities of the different techniques are analyzed. The main contribution of this overview paper is to synthesize and organize information, identify trends, and provide a comprehensive understanding of sitting posture diagnosis systems, offering researchers an accessible resource for navigating the current state of knowledge of this particular field.

Shared control algorithms have emerged as a promising approach for enabling real-time driver automated system cooperation in automated vehicles. These algorithms allow human drivers to actively participate in the driving process while receiving continuous assistance from the automated system in specific scenarios. However, despite the theoretical benefits being analyzed in various works, further demonstrations of the effectiveness and user acceptance of these approaches in real-world scenarios are required due to the involvement of the human driver in the control loop. Given this perspective, this paper presents and analyzes the results of a simulator-based study conducted to evaluate a shared control algorithm for a critical lateral maneuver. The maneuver involves the automated system helping to avoid an oncoming motorcycle that enters the vehicle’s lane. The study’s goal is to assess the algorithm’s performance, safety, and user acceptance within this specific scenario. For this purpose, objective measures, such as collision avoidance and lane departure prevention, as well as subjective measures related to the driver’s sense of safety and comfort are studied. In addition, three levels of assistance (gentle, intermediate, and aggressive) are tested in two driver state conditions (focused and distracted). The findings have important implications for the development and execution of shared control algorithms, paving the way for their incorporation into actual vehicles.

To enable safe and efficient use of multi-robot systems in everyday life, a robust and fast method for coordinating their actions must be developed. In this paper, we present a distributed task allocation and scheduling algorithm for missions where the tasks of different robots are tightly coupled with temporal and precedence constraints. The approach is based on representing the problem as a variant of the vehicle routing problem, and the solution is found using a distributed metaheuristic algorithm based on evolutionary computation (CBM-pop). Such an approach allows a fast and near-optimal allocation and can therefore be used for online applications. Simulation results show that the approach has better computational speed and scalability without loss of optimality compared to the state-of-the-art distributed methods. An application of the planning procedure to a practical use case of a greenhouse maintained by a multi-robot system is given.

Cloud Computing is revolutionizing smart manufacturing by offering on-demand and scalable computer systems that facilitate plant data analysis and operational efficiency optimization. DevOps is a methodology, widely used for developing Cloud Computing systems, that streamlines software development by improving its integration, delivery, and deployment. Although cloud application designers within a DevOps team are assumed to have development and operational knowledge, this does not fall within the skills of experts that design analytics applications of plant data. The deployment environment is also relevant since, as such applications are often hosted in the Fog, the proliferation of application components may hinder their composition and validation. This work is aimed at embracing the Platform Engineering approach to provide a tailored toolkit that guides the design and development of OpenFog compliant applications for the experts in the Smart Manufacturing domain. The platform uses Model Driven Engineering techniques and a flow-based visual editor to allow application designers to graphically compose applications from components previously delivered by component developers, abstracting them from the underlying technologies. As a result, containerized applications, ready to be deployed and run by a container orchestrator, are obtained. The feasibility of the proposal is proved through an industrial case study.

An actuator is a device that moves or controls a mechanism, by turning a control signal into mechanical action, such as in an electric motor [...]

Una de las tecnologías mas atractivas y actualmente en auge que se esta desarrollando rápidamente es el Gemelo Digital (Digital Twin en inglés, DT). Es bien conocido como un habilitador para la Industria 4.0. Tanto en la comunidad científica como industrial, el concepto, la tecnología y las aplicaciones asociadas al mismo, van generando controversia. Sigue habiendo una gran variedad de definiciones del mismo concepto. Aparentemente no parece haber una comprensión común de este término en la literatura. Se utiliza de forma diferente en diferentes disciplinas. La simulación basada en modelos ha sido, desde hace mucho tiempo, una herramienta común para el diseño en una fase inicial de planificación, pero no durante el tiempo de trabajo del sistema ya diseñado. En este trabajo se pretende abarcar una revisión histórica de este concepto. Mientras que muchas revisiones bibliográficas existentes se centran principalmente en la industria de manufactura, este artículo hará un enfoque en aplicaciones de los gemelos digitales en el campo de la Automática., One of the most attractive and currently booming technologies that is rapidly developing is the Digital Twin (DT). It is wellknown as an enabler for Industry 4.0. In both the scientific and industrial community, the concept, the technology and the applica-tions associated with it, are generating more and more controversy. There is still a wide variety of definitions of the same concept.There does not seem to be a common understanding of the term in the literature. It is used differently in different disciplines.Model-based simulation has long been a common tool for design in an initial planning phase, but not during the working time ofthe designed system. This paper aims to provide a historical review of this concept. While many reviews of existing literature focusmainly on the manufacturing industry, this paper will focus on the applications of digital twins in the field of automatic control.

The technological development in the area of power electronics has paved the way for the construction of High Voltage Direct Current (HVDC) systems. The utilization of HVDC grids alongside conventional High Voltage Alternating Current (HVAC) grids poses several challenges, especially, from stability and control points of view. Indeed, moving towards such systems in the context of conventional Alternating Current (AC) power systems cannot be possible without ensuring the overall stability of hybrid HVAC/HVDC grids. This paper analyzes different aspects of the stability of Voltage Source Converter (VSC)-based HVDC grids and presents various methods of improving stability based on a systematic and comprehensive review. In addition, this paper provides a concise classification of various control methods to improve the operation of such grids and the advantages of each method.

This article presents a distributed model predictive controller with time-varying partitioning based on the augmented Lagrangian alternating direction inexact Newton method (ALADIN). In particular, we address the problem of controlling the temperature of a heat transfer fluid (HTF) in a set of loops of solar parabolic collectors by adjusting its flow rate. The control problem involves a nonlinear prediction model, decoupled inequality constraints, and coupled affine constraints on the system inputs. The application of ALADIN to address such a problem is combined with a dynamic clustering-based partitioning approach that aims at reducing, with min-imum performance losses, the number of variables to be coordinated. Numerical results on a 10-loop plant are presented.

The impact of mechanical ventilation on airborne diseases is not completely known. The recent pandemic of COVID-19 clearly showed that additional investigations are necessary. The use of computational tools is an advantage that needs to be included in the study of designing safe places. The current study focused on a hospital lift where two subjects were included: a healthy passenger and an infected one. The elevator was modelled with a fan placed on the middle of the ceiling and racks for supplying air at the bottom of the lateral wall. Three ventilation strategies were evaluated: a without ventilation case, an upwards-blowing exhausting fan case and a downwards-blowing fan case. Five seconds after the elevator journey began, the infected person coughed. For the risk assessment, the CO2 concentration, droplet removal performance and dispersion were examined and compared among the three cases. The results revealed some discrepancies in the selection of an optimal ventilation strategy. Depending on the evaluated parameter, downward-ventilation fan or no ventilation strategy could be the most appropriate approach.

The expansion of floating offshore wind brings the industry closer to achieving commercial viability. However, the challenging environment characterised by strong winds, waves, and currents, along with the growing size of wind turbines and the dynamic behaviour of floaters, introduces concerns about power production efficiency and system durability due to increased fatigue loads, which subsequently impacts overall costs. In an attempt to mitigate the financial implications coming from alterations made to control strategies and structural elements during the initial design phase, this paper propounds an all-encompassing simulation framework for offshore wind turbines. The current study thoroughly explores the various capabilities of the tool, with a focus on its simulation models. Importantly, the paper highlights the complex interactions between tool models and different controllers. Carefully designed, this tool offers users a variety of functions to enhance system design, fine-tune control strategies, and thoroughly assess performance metrics. The paper elaborates on these aspects, providing an explanation of the tool's capabilities and enhancing the dynamic comparison between the models.

Solar radiation data play a pivotal role in harnessing solar energy. Unfortunately, the availability of these data is limited due to the sparse distribution of meteorological stations worldwide. This paper introduces and simulates three models designed for estimating and predicting global solar radiation at ground level. Furthermore, it conducts an in-depth analysis and comparison of the simulation results derived from these models, utilizing measured data from selected sites in Algeria where such information is accessible. The focus of our study revolves around three empirical models: Capderou, Lacis and Hansen, and Liu and Jordan. These models utilize day number and solar factor as input parameters, along with the primary site’s geographical coordinates—longitude, latitude, and altitude. Additionally, meteorological parameters such as relative humidity, temperature, and pressure are incorporated into the models. The objective is to estimate global solar radiation for any given day throughout the year at the specified location. Upon simulation, the results highlight that the Capderou model exhibits superior accuracy in approximating solar components, demonstrating negligible deviations between real and estimated values, especially under clear-sky conditions. However, these models exhibit certain limitations in adverse weather conditions. Consequently, alternative approaches, such as fuzzy logic methods or models based on satellite imagery, become essential for accurate predictions in inclement weather scenarios.

In order to smoothly connect to permanently disturbed grids, DFIG-based wind turbines must precisely synchronize the voltage induced at their open stator with that of the grid. Hence, aiming at addressing the still unpublished task of synchronizing DFIGs to simultaneously unbalanced and harmonically distorted grids, a phase-locked loop (PLL)-less and naturally chatter-free sliding-mode control (SMC) algorithm is proposed. The strategies developed so far were formulated considering synchronous reference frames. However, by designing a stationary reference frame-based solution, decomposition into positive- and negative-sequences and harmonic components is avoided. As a result, a relatively straightforward control structure with strong potential for industrialization is obtained, consisting of a single voltage loop per component with just one parameter to be tuned. The stability and robustness resulting from its application are analytically studied under both uncertainties and disturbances. Additionally, a simple method for rotor positioning, independent of grid disturbances, is provided. Simulation over a 2-MW DFIG model and rapid control prototyping (RCP) over a 7-kW DFIG experimental rig are carried out. In this way, the performance and robustness of the suggested control scheme are validated under both unbalanced and harmonically distorted grid voltage, substantial parameter deviations, and varying wind speed and grid frequency profiles.

En este video se realiza una guía de cómo utilizar el software de visión artificial Sherlock para utilizar la herramienta scripts. Los objetivos son que aprendáis a: - Conocer la sintaxis básica de javascript - Usar y depurar scripts. - Intercambiar información entre Javascript y Sherlock

En este vídeo se detalla la arquitectura de un PLC industrial así como su funcionamiento durante la ejecución del automatismo.

En este vídeo se muestra cómo agregar OBs de interrupción y periódicos en un proyecto de TIA Portal.

En este vídeo se presenta el concepto de remanencia en TIA Portal. Seguidamente, se muestra cómo emplearlo en variables de memoria así como en contadores y temporizadores.

En este vídeo se muestra cómo crear y emplear un OB de arranque en un proyecto de TIA Portal.

En este vídeo se muestra cómo utilizar las tablas de observación y forzado de TIA Portal. En concreto, podrás mostrar valores de diferentes variables así cómo poder forzarlas para modificar el funcionamiento del automatismo. Esto es válido tanto para una prueba sobre un autómata físico como para el simulado con PLC Sim.

En este vídeo se detalla el procedimiento a seguir para simular un automatismo implementado en TIA Portal mediante la herramienta PLC Sim.

En este vídeo se muestra cómo activar y acceder vía web el servidor web de un autómata Siemens.