Normative reference of standing long jump for Colombian schoolchildren aged 9-17.9 years: The FUPRECOL study

El propósito del presente estudio era generar los valores normativos de salto largo para niños de 9-17.9 años, e investigar las diferencias de sexo y grupo de edad

HVDC Power Transmission Simulation for Offshore Wind System with Three-Level Converter

An integrated mathematical model for the simulation of an offshore wind system performance is presented in this paper. The mathematical model considers an offshore variable-speed turbine in deep water equipped with a permanent magnet synchronous generator using multiple point full-power clamped three-level converter, converting the energy of a variable frequency source in injected energy into the electric network with constant frequency, through a HVDC transmission submarine cable. The mathematical model for the drive train is a concentrate two mass model which incorporates the dynamic for the blades of the wind turbine, tower and generator due to the need to emulate the effects of the wind and the floating motion. Controller strategy considered is a proportional integral one. Also, pulse width modulation using space vector modulation supplemented with sliding mode is used for trigger the transistors of the converter. Finally, a case study is presented to access the system performance.

Rapid Control Prototyping of an L2+ Highway Assist System

Advanced Driver Assistance Systems (ADAS) are proving to have huge potential in road safety, comfort, and efficiency. In recent years, car manufacturers have equipped their high-end vehicles with Level 2 ADAS, which are, according to SAE International, systems that combine both longitudinal and lateral active motion control. These automated driving features, while only available in highway scenarios, appear to be very promising towards the introduction of hands-free driving. However, as they rely only on an on-board sensor suite, their continuative operation may be affected by the current environmental conditions: this prevents certain functionalities such as the automated lane change, other than requiring the driver to keep constantly the hands on the steering wheel. The enabling factor for hands-free highway driving proposed by Mobileye is the integration of high-definition maps, thus leading to the so-called Level 2+. This thesis was carried out during an internship in Maserati's Virtual Engineering team. The activity consisted of the design of an L2+ Highway Assist System following the Rapid Control Prototyping approach, starting from the definition of the requirements up to the real-time implementation and testing on a simulator of the brand new compact SUV Maserati Grecale. The objective was to enhance the current Level 2 highway driving assistance system with hands-free driving capability; for this purpose an Autonomous Lane Change functionality has been designed, proposing a Model Predictive Control-based decision-maker, in charge of assessing both the feasibility and convenience of performing a lane-change maneuver. The result is a Highway Assist System capable of driving the vehicle in a traffic scenario safely and efficiently, never requiring driver intervention.

Distributed optimization and games over networks: a system theoretical perspective

Several decision and control tasks involve networks of cyber-physical systems that need to be coordinated and controlled according to a fully-distributed paradigm involving only local communications without any central unit. This thesis focuses on distributed optimization and games over networks from a system theoretical perspective. In the addressed frameworks, we consider agents communicating only with neighbors and running distributed algorithms with optimization-oriented goals. The distinctive feature of this thesis is to interpret these algorithms as dynamical systems and, thus, to resort to powerful system theoretical tools for both their analysis and design. We first address the so-called consensus optimization setup. In this context, we provide an original system theoretical analysis of the well-known Gradient Tracking algorithm in the general case of nonconvex objective functions. Then, inspired by this method, we provide and study a series of extensions to improve the performance and to deal with more challenging settings like, e.g., the derivative-free framework or the online one. Subsequently, we tackle the recently emerged framework named distributed aggregative optimization. For this setup, we develop and analyze novel schemes to handle (i) online instances of the problem, (ii) ``personalized'' optimization frameworks, and (iii) feedback optimization settings. Finally, we adopt a system theoretical approach to address aggregative games over networks both in the presence or absence of linear coupling constraints among the decision variables of the players. In this context, we design and inspect novel fully-distributed algorithms, based on tracking mechanisms, that outperform state-of-the-art methods in finding the Nash equilibrium of the game.

Diffusive models and chaos indicators for non-linear betatron motion in circular hadron accelerators

Understanding the complex dynamics of beam-halo formation and evolution in circular particle accelerators is crucial for the design of current and future rings, particularly those utilizing superconducting magnets such as the CERN Large Hadron Collider (LHC), its luminosity upgrade HL-LHC, and the proposed Future Circular Hadron Collider (FCC-hh). A recent diffusive framework, which describes the evolution of the beam distribution by means of a Fokker-Planck equation, with diffusion coefficient derived from the Nekhoroshev theorem, has been proposed to describe the long-term behaviour of beam dynamics and particle losses. In this thesis, we discuss the theoretical foundations of this framework, and propose the implementation of an original measurement protocol based on collimator scans in view of measuring the Nekhoroshev-like diffusive coefficient by means of beam loss data. The available LHC collimator scan data, unfortunately collected without the proposed measurement protocol, have been successfully analysed using the proposed framework. This approach is also applied to datasets from detailed measurements of the impact on the beam losses of so-called long-range beam-beam compensators also at the LHC. Furthermore, dynamic indicators have been studied as a tool for exploring the phase-space properties of realistic accelerator lattices in single-particle tracking simulations. By first examining the classification performance of known and new indicators in detecting the chaotic character of initial conditions for a modulated Hénon map and then applying this knowledge to study the properties of realistic accelerator lattices, we tried to identify a connection between the presence of chaotic regions in the phase space and Nekhoroshev-like diffusive behaviour, providing new tools to the accelerator physics community.

Study of the tracking performance of a liquid Argon detector based on a novel optical imaging concept

The Deep Underground Neutrino Experiment (DUNE) is a long-baseline accelerator experiment designed to make a significant contribution to the study of neutrino oscillations with unprecedented sensitivity. The main goal of DUNE is the determination of the neutrino mass ordering and the leptonic CP violation phase, key parameters of the three-neutrino flavor mixing that have yet to be determined. An important component of the DUNE Near Detector complex is the System for on-Axis Neutrino Detection (SAND) apparatus, which will include GRAIN (GRanular Argon for Interactions of Neutrinos), a novel liquid Argon detector aimed at imaging neutrino interactions using only scintillation light. For this purpose, an innovative optical readout system based on Coded Aperture Masks is investigated. This dissertation aims to demonstrate the feasibility of reconstructing particle tracks and the topology of CCQE (Charged Current Quasi Elastic) neutrino events in GRAIN with such a technique. To this end, the development and implementation of a reconstruction algorithm based on Maximum Likelihood Expectation Maximization was carried out to directly obtain a three-dimensional distribution proportional to the energy deposited by charged particles crossing the LAr volume. This study includes the evaluation of the design of several camera configurations and the simulation of a multi-camera optical system in GRAIN.

On the motion planning & control of nonlinear robotic systems

In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance.

Study of the rotational state of Titan using radio tracking data of the Dragonfly mission

Our solar system contains an impressive amount of celestial bodies. For example Saturn posses a huge variety of natural satellites, the diversity in size and physical proprieties of which might amaze imagination. The observational data gathered in 30 years range of deep space missions revealed, that some of these bodies can hide subsurface oceans under their crust. The water, as we know, serves as a fundamental base for a possible appearance of life. This statement is quite exited for the scientific society and serves as a reason for studying so called ”ocean worlds”. In order to detect the celestial bodies with the hidden subsurface ocean, one of the key aspects is the study of their rotational state, which is strongly coupled with the body internal structure. It can be done through the various techniques mentioned in Chapter 1. The main goal of the thesis is the study of rotational state of Titan, whose interior structure expectedly contains liquid ocean layer under its icy crust. Titan is the largest moon of Saturn and it is the second largest moon in the solar system in general. This natural satellite is of particular scientific interest, because it is one of a kind which has substantial atmosphere. The present work was done using radio tracking data of the Dragonfly mission which is one of the next NASA’s missions destined for Titan selected as a part of the New Frontiers Program in 2019. The detailed characteristic of the Dragonfly regarding the landing site and mission lifetime was reported in Chapter 2. The radio-tracking communication link from Titan side was performed using Dragonfly X band transponder according to the schedule tracking opportunity. From Earth side according to the mission, Deep Space Station 25 which is a part of NASA’s Deep Space Network was considered. Only Doppler data was used for studying Titan rotational state, even though there are other reliable techniques described in Chapter 3, that in general could be implemented.

Modeling and Model Predictive Control of an Industrial Hydraulic System

This thesis aims to illustrate the construction of a mathematical model of a hydraulic system, oriented to the design of a model predictive control (MPC) algorithm. The modeling procedure starts with the basic formulation of a piston-servovalve system. The latter is a complex non linear system with some unknown and not measurable effects that constitute a challenging problem for the modeling procedure. The first level of approximation for system parameters is obtained basing on datasheet informations, provided workbench tests and other data from the company. Then, to validate and refine the model, open-loop simulations have been made for data matching with the characteristics obtained from real acquisitions. The final developed set of ODEs captures all the main peculiarities of the system despite some characteristics due to highly varying and unknown hydraulic effects, like the unmodeled resistive elements of the pipes. After an accurate analysis, since the model presents many internal complexities, a simplified version is presented. The latter is used to linearize and discretize correctly the non linear model. Basing on that, a MPC algorithm for reference tracking with linear constraints is implemented. The results obtained show the potential of MPC in this kind of industrial applications, thus a high quality tracking performances while satisfying state and input constraints. The increased robustness and flexibility are evident with respect to the standard control techniques, such as PID controllers, adopted for these systems. The simulations for model validation and the controlled system have been carried out in a Python code environment.

Loading and damage modelling for an integrated SHM system of a prestressed concrete railway bridge in Naples

The thesis explores recent technology developments in the field of structural health monitoring and its application to railway bridge projects. It focuses on two main topics. First, service loads and effect of environmental actions are modelled. In particular, the train moving load and its interaction with rail track is considered with different degrees of detail. Hence, results are compared with real-time experimental measurements. Secondly, the work concerns the identification, definition and modelling process of damages for a prestressed concrete railway bridge, and their implementation inside FEM models. Along with a critical interpretation of the in-field measurements, this approach results in the development of undamaged and damaged databases for the AI-aided detection of anomalies and the definition of threshold levels to prompt automatic alert interventions. In conclusion, an innovative solution for the development of the railway weight-in-motion system is proposed.

An Embedded In-Cabin Lightweight High-Performance 3D Gaze Estimation System

Gaze estimation has gained interest in recent years for being an important cue to obtain information about the internal cognitive state of humans. Regardless of whether it is the 3D gaze vector or the point of gaze (PoG), gaze estimation has been applied in various fields, such as: human robot interaction, augmented reality, medicine, aviation and automotive. In the latter field, as part of Advanced Driver-Assistance Systems (ADAS), it allows the development of cutting-edge systems capable of mitigating road accidents by monitoring driver distraction. Gaze estimation can be also used to enhance the driving experience, for instance, autonomous driving. It also can improve comfort with augmented reality components capable of being commanded by the driver's eyes. Although, several high-performance real-time inference works already exist, just a few are capable of working with only a RGB camera on computationally constrained devices, such as a microcontroller. This work aims to develop a low-cost, efficient and high-performance embedded system capable of estimating the driver's gaze using deep learning and a RGB camera. The proposed system has achieved near-SOTA performances with about 90% less memory footprint. The capabilities to generalize in unseen environments have been evaluated through a live demonstration, where high performance and near real-time inference were obtained using a webcam and a Raspberry Pi4.

Development of a Robotic Wires Storage System for Switchgear Manufacturing Automation

Considering the great development of robotics in industrial automation, the Remodel project aims to reproduce, through the use of Cobots, the wiring activity typical of a human operator and to realize an autonomous storage work. My researches focused on this second topic. In this paper, we will see how to realize a gripper compatible with an Omron TM5X-900, able to perform a pick and place of different types of cables, but also how to compute possible trajectories. In particular, what I needed, was a trajectory going from the Komax, the cables production machine, to a Warehouse taking into account the possible entangles of cables with the robot during its motion. The last part has been dedicated to the synchronization between robot and main machine work.

Development of a state-variable filter for a motion control application.

In collaboration with G.D. SpA I attended an internship with the purpose of developing a filter for the position control of industrial machines during testing and maintenance operations. The filter elaborates a signal in position provided by an electonic handwheel, in order to enable the application to be controlled with a signal in velocity with arbitrarily dynamics chosen during the design phase. Limiting the dynamics of the filter provide a more stable and less demanding reference trajectory which reduce the vibrations and tracking errors of the motor controlled by it. It also prevents misusages of the handwheel from the technician which could end up in harmful interferences between the mechanical parts moved by the handwheel.

Random Access Procedures in 5G IoT via NTN: System level performances

The Internet of Things (IoT) is a critical pillar in the digital transformation because it enables interaction with the physical world through remote sensing and actuation. Owing to the advancements in wireless technology, we now have the opportunity of using their features to the best of our abilities and improve over the current situation. Indeed, the Internet of Things market is expanding at an exponential rate, with devices such as alarms and detectors, smart metres, trackers, and wearables being used on a global scale for automotive and agriculture, environment monitoring, infrastructure surveillance and management, healthcare, energy and utilities, logistics, good tracking, and so on. The Third Generation Partnership Project (3GPP) acknowledged the importance of IoT by introducing new features to support it. In particular, in Rel.13, the 3GPP introduced the so-called IoT to support Low Power Wide Area Networks (LPWAN).As these devices will be distributed in areas where terrestrial networks are not feasible or commercially viable, satellite networks will play a complementary role due to their ability to provide global connectivity via their large footprint size and short service deployment time. In this context, the goal of this thesis is to investigate the viability of integrating IoT technology with satellite communication (SatCom) systems, with a focus on the Random Access(RA) Procedure. Indeed, the RA is the most critical procedure because it allows the UE to achieve uplink synchronisation, obtain the permanent ID, and obtain uplink transmission resources. The goal of this thesis is to evaluate preamble detection in the SatCom environment.

Study of an advanced transport system exploiting magnetic levitation: the Beckhoff XPlanar

The transport system is one of the most important components to be chosen in the design of an automatic machine. There is a wide variety of different choices that can be made in picking this element, each one having its own strengths and its own drawbacks. If it is desired to obtain some elaborate behaviour from the transport system, it is a good idea to think about some flexible and advanced solutions. Among these transport systems, the newest is the Beckhoff XPlanar. This transport system exploits magnetic levitation to move some passive magnetic movers on a completely customizable plane, in an entirely contact-free way. This provides a fast, clean, and noiseless motion, which is extremely desirable in a modern automatic machine. The purpose of this Thesis is to analyse the potentialities and the problems of this new device, starting from the basics. After having presented in detail the topic, an analysis on the hardware components needed to build this system is performed. Then, it is conducted a study on the concepts needed to know how to build a controller having the purpose of dealing with this system. After that, the various types of motion are studied and executed and, later on, some experiments on the real kit are carried out. These studies start from the diagnostic and involve other analyses that are used to test the limits of this transport system. In performing these analyses, it is noticed how the kit presents some problems in reaching the limits of the dynamics. Finally, two different types of station cycle are implemented, which are useful to get a rough idea on the potentialities of this new advanced transport system.