This thesis details the implementation of two adaptive controllers on autonomous underwater vehicle(AUV) attitude dynamics starting from the standard six degree-of-freedom dynamic model. I apply two model reference adaptive control (MRAC) algorithms which make use of kernel functions for learning functional uncertainty present in the system dynamics. The first method extends recent results on model reference adaptive control using reproducing kernel Hilbert space (RKHS) learning techniques for some general cases of multi-input systems. The first controller design is a model reference adaptive controller (MRAC) based on a vector- valued RKHS that is induced by operator-valued kernels. This paper formulates a model reference adaptive control strategy based on a dead zone robust modification, and derives conditions for the ultimate boundedness of the tracking error in this case. The second controller is an implementation of the Gaussian Process MRAC developed by Chowdhary, et al. I discuss the method of each of these algorithms before contrasting the underlying theoretical structure of each algorithm. Finally, I provide a comparison of each algorithm's performance on the six degree-of-freedom dynamic model of the Virginia Tech 690 AUV and provide field trial results for the RKHS based MRAC implementation. / Master of Science / This thesis details the implementation of two algorithms which control the attitude of an autonomous underwater vehicle. Rather than developing detailed dynamic models of the vehicles as is performed in classical control methods, each of these implementations only makes assumptions that the unknown portions of the dynamic models can be represented by a broad class of functions defined by a mathematical structure called a reproducing kernel Hilbert Space. Each algorithm implements learning techniques using the theory of reproducing kernel Hilbert spaces to bound the error between the vehicle attitude and the commanded vehicle attitude. One algorithm, called RKHS MRAC, implements an adaptive update law based on the attitude error to improve the controller performance. The second algorithm, called GP MRAC, uses estimated vehicle rotational accelerations and statistical learning methods to approximate the unknown function. Each of these methods is compared in theory and in a vehicle simulation. The RKHS MRAC is additionally demonstrated in field trial results.

In this thesis we demonstrate a technique for robust controller design for an autonomous underwater vehicle (AUV) that explicitly handles the trade-off between reference tracking, agility, and energy efficient performance. AUVs have many sources of modeling uncertainty that impact the uncertainty in maneuvering performance. A robust control design process is proposed to handle these uncertainties while meeting control system performance objectives. We investigate the relationships between linear system design parameters and the control performance of our vehicle in order to inform an H∞ controller synthesis problem with the objective of balancing these tradeoffs. We evaluate the controller based on its reference tracking performance, agility and energy efficiency, and show the efficacy of our control design strategy. / Master of Science / In this thesis we demonstrate a technique for autopilot design for an autonomous underwater vehicle (AUV) that explicitly handles the trade-off between three performance metrics. Mathematical models of AUVs are often unable to fully describe their many physical properties. The discrepancies between the mathematical model and reality impact how certain we can be about an AUV's behavior. Robust controllers are a class of controller that are designed to handle uncertainty. A robust control design process is proposed to handle these uncertainties while meeting vehicle performance objectives. We investigate the relationships between design parameters and the performance of our vehicle. We then use this relationship to inform the design of a controller. We evaluate this controller based on its energy efficiency, agility and ability to stay on course, and thus show the effectiveness of our control design strategy.

Navigation of autonomous underwater vehicles (AUVs) in the subsea environment is particularly challenging due to the unavailability of GPS because of rapid attenuation of electromagnetic waves in water. As a result, the AUV requires alternative methods for position estimation. This thesis describes a terrain-aided navigation approach for an AUV where, with the help of a prior depth map, the AUV localizes itself using altitude measurements from a multibeam DVL. The AUV simultaneously builds a probabilistic depth map of the seafloor as it moves to unmapped locations. The main contribution of this thesis is a new, scalable, and on-line terrain-aided navigation solution for AUVs which does not require the assistance of a support surface vessel. Simulation results on synthetic data and experimental results from AUV field trials in Panama City, Florida are also presented. / Master of Science

Of all of the bodies in the solar system, Europa is perhaps the most enticing. Based on several lines of evidence, Europa, a moon of Jupiter, is believed to have an ocean of liquid water beneath several kilometers of ice. This ocean is likely in contact with Europa's rocky core, making Europa's ocean one of the most likely places for life to exist in the solar system outside of Earth. This thesis provides an outline of the technology required for a mission that travels to Europa, penetrates the ice, and explores the ocean below. In order to create this outline, this thesis first provides background on previous missions to the outer planets. A discussion of the science requirements is presented and then a value system by which designs are evaluated is developed. Current technologies and the design alternatives are presented and evaluated using the value system. A final mission architecture and concept of operations are then presented. / Master of Science

The primary objective of this research is to investigate the viability of magnetic anomaly localization with an autonomous underwater vehicle, using a genetic algorithm (GA). The localization method, first proposed by Sheinker. et al. 2008, is optimized here for the case of a moving platform. Extensive magnetic field modeling and algorithm simulation has been conducted and yields promising results. Field testing of the method is conducted with the use of the Ocean Floor Geophysics Self-Compensating Magnetometer (SCM). Extensive out-of-water field testing is conducted to validate the ability to measure a target signal in a uniform NED frame as well as to validate the effectiveness of the GA. The outcome of the simulation closely matches the results of the conducted field tests. Additionally, the SCM is fully integrated with FAU’s Remus 100 AUV and preliminary in-water testing of the system has been conducted. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

This research addresses the problem of allocating closely spaced targets to multiple autonomous underwater vehicles (AUV) in the presence of constant ocean currents. The main difficulty of this problem is that the non-holonomic vehicles are constrained to move along forward paths with bounded curvatures. The Dubins model is a simple but effective way to handle the kinematic characteristics of AUVs. It gives complete characterization of the optimal paths between two configurations for a vehicle with limited turning radius moving in a plane at constant speed. In the proposed algorithm, Dubins paths are modified to include ocean currents, resulting in paths defined by curves whose radius of curvature is not constant. To determine the time required to follow such paths, an approximate dynamic model of the AUV is queried due to the computational complexity of the full model. The lower order model is built from data obtained from sampling the full model. The full model is used in evaluating the final tour times of the sequences generated by the proposed algorithm to validate the results. The proposed algorithm solves the task allocation problem with market-based auctions that minimize the total travel time to complete the mission. The novelty of the research is the path cost calculation that combines a Dubins model, an AUV dynamic model, and a model of the ocean current. Simulations were conducted in Matlab to illustrate the performance of the proposed algorithm using various number of task points and AUVs. The task points were generated randomly and uniformly close together to highlight the necessity for considering the curvature constraints. For a sufficiently dense set of points, it becomes clear that the ordering of the Euclidean tours are not optimal in the case of the Dubins multiple travelling salesmen problem. This is due to the fact that there is little relationship between the Euclidean and Dubins metrics, especially when the Euclidean distances are small with respect to the turning radius. An algorithm for the Euclidean problem will tend to schedule very close points in a successive order, which can imply long maneuvers for the AUV. This is clearly demonstrated by the numerous loops that become problematic with dense sets of points. The algorithm proposed in this thesis does not rely on the Euclidean solution and therefore, even in the presence of ocean currents, can create paths that are feasible for curvature bound vehicles. Field tests were also conducted on an Iver2 AUV at the Avila Pier in California to validate the performance of the proposed algorithm in real world environments. Missions created based on the sequences generated by the proposed algorithm were conducted to observe the ability of an AUV to follow paths of bounded curvature in the presence of ocean currents. Results show that the proposed algorithm generated paths that were feasible for an AUV to track closely, even in the presence of ocean current.

This research addresses the problem of allocating closely spaced targets to multiple autonomous underwater vehicles (AUV) in the presence of constant ocean currents. The main difficulty of this problem is that the non-holonomic vehicles are constrained to move along forward paths with bounded curvatures. The Dubins model is a simple but effective way to handle the kinematic characteristics of AUVs. It gives complete characterization of the optimal paths between two configurations for a vehicle with limited turning radius moving in a plane at constant speed. In the proposed algorithm, Dubins paths are modified to include ocean currents, resulting in paths defined by curves whose radius of curvature is not constant. To determine the time required to follow such paths, an approximate dynamic model of the AUV is queried due to the computational complexity of the full model. The lower order model is built from data obtained from sampling the full model. The full model is used in evaluating the final tour times of the sequences generated by the proposed algorithm to validate the results. The proposed algorithm solves the task allocation problem with market-based auctions that minimize the total travel time to complete the mission. The novelty of the research is the path cost calculation that combines a Dubins model, an AUV dynamic model, and a model of the ocean current. Simulations were conducted in Matlab to illustrate the performance of the proposed algorithm using various number of task points and AUVs. The task points were generated randomly and uniformly close together to highlight the necessity for considering the curvature constraints. For a sufficiently dense set of points, it becomes clear that the ordering of the Euclidean tours are not optimal in the case of the Dubins multiple travelling salesmen problem. This is due to the fact that there is little relationship between the Euclidean and Dubins metrics, especially when the Euclidean distances are small with respect to the turning radius. An algorithm for the Euclidean problem will tend to schedule very close points in a successive order, which can imply long maneuvers for the AUV. This is clearly demonstrated by the numerous loops that become problematic with dense sets of points. The algorithm proposed in this thesis does not rely on the Euclidean solution and therefore, even in the presence of ocean currents, can create paths that are feasible for curvature bound vehicles. Field tests were also conducted on an Iver2 AUV at the Avila Pier in California to validate the performance of the proposed algorithm in real world environments. Missions created based on the sequences generated by the proposed algorithm were conducted to observe the ability of an AUV to follow paths of bounded curvature in the presence of ocean currents. Results show that the proposed algorithm generated paths that were feasible for an AUV to track closely, even in the presence of ocean current.

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. / -

The production of clean water, the generation of nuclear power and the development of chemicals, petro-chemicals and pharmaceuticals all rely on liquid-based processes. They are fundamental to modern society, however the real-time monitoring of such processes is an inherently difficult challenge which has not yet been satisfactorily solved.Current methods of monitoring include on- and off-line spot checks and industrial process tomography. Neither of these methods provides the spatial or temporal resolution required to properly characterise the processes. This research project proposes a new monitoring method for processes which can tolerate foreign objects; a mobile underwater sensor network (MUSN).An MUSN has the potential to increase both the spatial and temporal resolution of measurements and could be used in real-time. The network would be formed by a number of mobile sensor platforms, in the form of micro-autonomous underwater vehicles (uAUVs) which would communicate using acoustics. The demonstrator for the technology is for use in the monitoring of nuclear storage ponds.Current AUV technology is not suitable for use in enclosed environments such as storage ponds due to the size and maneuverability. This thesis presents the research conducted in the development of a new vehicle uAUV. The work presented covers the mechatronic aspects of the vehicle; the design of the hull, propulsion systems, corresponding control circuitry and basic motion control systems. One of the main factors influencing the design of the vehicle has been cost. If a large number of vehicles are used to form a network, the cost of an individual uAUV should be kept as low as possible. This has raised a number of technical challenges as low-cost components are often of low-tolerance. Imbalanced time-varying thrust, low manufacturing tolerances and noisy indirect sensor measurements for the control systems have all been overcome in the design of the vehicle. The outcome of the research is a fully functional prototype uAUV. The vehicle is spherical in shape with a diameter of approximately 15cm, with six thruster units mounted around the equator (increasing the horizontal clearance to 20cm) to provide thrust in four degrees of freedom (surge, sway, heave and yaw). The vehicle has a sensor suite which includes a pressure sensor, digital compass and a gyroscope which provide inputs to the motion control systems. The controllers have been developed and implemented on the vehicle's custom built embedded system. Experiments have been conducted showing that the uAUV is able to move in 3D with closed-loop control in heave and yaw. Motion in surge and sway is open-loop, via a dead-reckoning system.

The growing need for ocean surveillance and exploration has pushed the development of novel autonomous underwater vehicle (AUV) technology. A current trend is to make use of bio-inspired propulsor to increase the overall system efficiency and performance, an improvement that has deep implications in the dynamics of the system. The goal of this dissertation is to propose a generic robust control framework specific for bio-inspired autonomous underwater vehicles (BIAUV). These vehicles utilize periodic oscillation of a flexible structural component to generate thrust, a propulsion mechanism that can be tuned to operate under resonance and consequently improve the overall system efficiency. The control parameter should then be selected to keep the system operating in such a condition. Another important aspect is to have a controller design technique that can address the time-varying behaviors, structured uncertainties and system nonlinearities. To address these needs a robust, model-based, nonlinear controller design technique is presented, called digital sliding mode controller (DSMC), which also takes into account the discrete implementation of these laws using microcontrollers. The control law is implemented in the control of a jellyfish-inspired autonomous underwater vehicle. / Ph. D.