Το μεγαλύτερο μέρος της επιφάνεια του πλανήτη καλύπτεται από τους ωκεανούς. Η περιέργεια του ανθρώπου να εξερευνήσει και να καταλάβει το πώς λειτουργεί το περιβάλλον του, σε συνδυασμό με την αναζήτηση νέων πόρων, ώθησε τον άνθρωπο στον υδάτινο κόσμο. Δεδομένου του βάθους της θάλασσας, οι αρχικές αυτόνομες καταδύσεις, αλλά και οι καταδύσεις με την βοήθεια αναπνευστικών συσκευών δεν κάλυψαν παρά στο ελάχιστο την πρόσβαση στον κόσμο αυτό. Η ανάπτυξη κάποιου διαμεσολαβητή ήταν όχι μόνο χρήσιμη αλλά και απαραίτητη για να προσεγγίσουμε μεγάλα βάθη αλλά και επικίνδυνα, για τους δύτες, μέρη. Στην παρούσα εργασία παρουσιάζεται η χρησιμότητα των υποβρύχιων οχημάτων, σε διάφορους τομείς των ανθρώπινων δραστηριοτήτων. Αναπτύσσονται φυσικές έννοιες και βασικοί ορισμοί για την περιγραφή του περιβάλλοντος στο οποίο λειτουργούν τα υποβρύχια οχήματα. Στη συνέχεια γίνεται αναφορά των διαφόρων κατηγοριών των υποβρύχιων οχημάτων που έχουν αναπτυχθεί μέχρι σήμερα. Αναλύονται λεπτομερώς οι τεχνολογικές τους δυσκολίες, τα πλεονεκτήματα και τα μειονεκτήματα του κάθε είδους υποβρύχιου οχήματος, καθώς επίσης και οι τεχνολογικές εξελίξεις στον τομέα αυτό. Για παράδειγμα, οι ακουστικές επικοινωνίες, η υποβρύχια πλοήγηση και η αποφυγή εμποδίων, ώστε να καταστεί εφικτή η υποβρύχια εξερεύνηση. Τέλος, παρουσιάζονται τα σπουδαιότερα υποβρύχια οχήματα που έχουν κατασκευαστεί μέχρι σήμερα και έχουν οδηγήσει σε σημαντικές ανακαλύψεις στον υδάτινο κόσμο. / -

Made available in DSpace on 2017-07-10T17:11:48Z (GMT). No. of bitstreams: 1 Dissertacao Mariana Uzeda2.pdf: 3273824 bytes, checksum: cb0d125fc8aae9dfe673029b5f5a30a5 (MD5) Previous issue date: 2014-08-29 / This work presents a comparative study between four different sliding mode variable structure control strategies (SMVSC) applied to autonomous underwater vehicles (AUV) positioning in 6 DOF, under the influence of wind, waves and marine currents. The addressed strategies are the conventional CEV-MD control based on Lyapunov stability, the CEV-MD control based on the equivalent control, the CEV-MD control based on the input-output stability and the CEVMD adaptive control. The accomplished comparisons seek a satisfactory tradeoff between the tracking performance and the closed-loop system stability in light of eliminating the chattering phenomenon. In that sense, the analysis and synthesis of the respective SMVSC control laws is carried out fromthe Lyapunov Stability Theory and the Barbalat s Lemma. As well as numerical simulations are implemented to obtaining the respective performances of each SMVSC control strategy presented. / Este trabalho apresenta um estudo comparativo entre quatro diferentes estratégias de controle de estrutura variável por modos deslizantes (CEV-MD) aplicadas ao posicionamento de veículos subaquáticos autônomos (VSA) em 6 GDL, sob a influência de ventos, ondas e correntes marinhas. As estratégias abordadas são o controle CEV-MD convencional baseado na estabilidade de Lyapunov, o controle CEV-MD baseado no controle equivalente, o controle CEV-MD baseado na estabilidade entrada-saída e o controle CEV-MD adaptativo. As comparações realizadas visam a eliminação do do fenômeno do chattering buscando um compromisso satisfatório entre o desempenho de rastreamento e a estabilidade do sistema em laço fechado. Nesse sentido, a análise e síntese das respectivas leis de controle CEV-MD é realizada a partir da Teoria de Estabilidade de Lyapunov e do Lema de Barbalat. Assim como simulações numéricas são implementadas para a obtenção dos respectivos desempenhos de cada estratégia de controle CEV-MD apresentada.

<p dir="ltr">The growing movement toward sustainable use of ocean resources is driven by the pressing need to alleviate environmental and human stressors on the planet and its oceans. From monitoring the food web to supporting sustainable fisheries and observing environmental shifts to protect against the effects of climate change, ocean observations significantly impact the Blue Economy. Acknowledging the critical role of Autonomous Underwater Vehicles (AUVs) in achieving persistent ocean exploration, this research addresses challenges focusing on the limited energy and storage capacity of AUVs, introducing a comprehensive underwater docking solution with a specific emphasis on enhancing the terminal homing phase through innovative vision algorithms leveraging neural networks.</p><p dir="ltr">The primary goal of this work is to establish a docking procedure that is failure-tolerant, scalable, and systematically validated across diverse environmental conditions. To fulfill this objective, a robust dock detection mechanism has been developed that ensures the resilience of the docking procedure through \comment{an} improved detection in different challenging environmental conditions. Additionally, the study addresses the prevalent issue of data sparsity in the marine domain by artificially generating data using CycleGAN and Artistic Style Transfer. These approaches effectively provide sufficient data for the docking detection algorithm, improving the localization of the docking station.</p><p dir="ltr">Furthermore, this work introduces methods to compress the learned docking detection model without compromising performance, enhancing the efficiency of the overall system. Alongside these advancements, a station-keeping algorithm is presented, enabling the mobile docking station to maintain position and heading while awaiting the arrival of the AUV. To leverage the sensors onboard and to take advantage of the computational resources to their fullest extent, this research has demonstrated the feasibility of simultaneously learning docking detection and marine wildlife classification through multi-task and transfer learning. This multifaceted approach not only tackles the limitations of AUVs' energy and storage capacity but also contributes to the robustness, scalability, and systematic validation of underwater docking procedures, aligning with the broader goals of sustainable ocean exploration and the blue economy.</p>