Improving Seaglider Efficiency: An Analysis of Wing Shapes, Hull Morphologies, and Propulsion Methods

Autonomous underwater gliders are a family of autonomous underwater vehicles used for long-term observation of oceanic environments. These gliders leverage changes in buoyancy and the resulting vertical motion, to generate forward locomotion via hydrodynamic surfaces. In order to function for extended periods, these systems operate in a low-speed, low-drag regime. This research examines factors impacting the operational efficiencies of gliders, including morphological changes, configuration changes, and propulsion. An interesting question arises when considering the operational efficiencies of conventionally propelled systems at the operating speeds typical of gliders. Can a conventional propulsion system match the efficiency of an underwater glider buoyancy engine? A first-principles, energy-based approach to glider operations was derived and verified using real world data. The energy usage for buoyancy driven propulsion was then compared to conventional propulsion types. The results from these calculations indicate that a conventionally propelled autonomous underwater vehicle can compete with and in some cases outperform a buoyancy driven system given the proper propulsive efficiency

Time-optimal trajectory and robust adaptive control for hybrid underwater glider

The undersea environment is generally still a mystery for the human race, although it has been with us for a long time. To explore under the sea, the underwater glider is the efficient equipment capable of sustainable operation for several months. For faster and longer duration performance, a new design of underwater glider (UG) shaping ray type is proposed. To have the shortest settling time, a new design of time-optimal trajectory (TOT) for controlling the states of the ray-type hybrid underwater glider (RHUG) is proposed. And for the stable flight control, a robust adaptive controller is designed for the RHUG with unknown parameters and environmental disturbances. The heading dynamics of the RHUG is presented with linear and quadratic damping. A closed form solution of the heading dynamics is realized for designing the time-optimal trajectory. The conventional and super-twisting sliding mode control will be constructed for tracking this trajectory. The tracking performance considering the disturbance effect will be discussed in simulations. For identification of unknown parameters of the system, the adaptive control is designed and implemented by the heading experiment. The RHUG uses the net buoyancy force for gliding under the water, so the depth control is essential. In this dissertation, a robust control algorithm with TOT will be carried out for the heaving motion using a hybrid actuation of the buoyancy engine and the propeller. The net buoyancy force with a constant rate is generated by the buoyancy engine for both descending and ascending motion. And the second actuator for the depth control is the propeller with quick response in producing thrusting force. To apply the robust control with TOT, the control input is designed for the buoyancy engine and thruster individually. And finally, the robust control with TOT using the buoyancy engine and thruster is simulated with consideration of external disturbances. When the RHUG is the underactuated system, a robust adaptive control is designed for the RHUG dynamics based on Lyapunov’s direct method using the backstepping and sliding mode control techniques. The performance of this controller is simulated for gliding motion and depth control with unknown parameters and bounded disturbances.Contents Contents i List of Tables iv List of Figures v Chapter 1. Introduction 1 1.1. Hybrid underwater glider 1 1.2. Time-optimal trajectory 4 1.3. Nonlinear control design 5 Chapter 2. Dynamics of RHUG 8 2.1 Dynamics of underwater vehicles 8 2.2 Design of RHUG platform 11 2.2.1 Hull design 11 2.2.2 Buoyancy engine and mass-shifter 12 2.2.3 Battery 13 2.2.4 Sensors 14 2.2.5 Assembly 16 2.3 Dynamics of RHUG 17 2.4 Hydrodynamic coefficients 19 2.5 Thruster modeling 21 2.6 Buoyancy engine modeling 22 2.7 Mass-shifter modeling 23 Chapter 3. Time-optimal trajectory with actuator saturation for heading control 25 3.1 Time-optimal trajectory 25 3.2 Heading motion 25 3.3 Analytic solution of heading dynamic equation 26 3.3.1 Right-hand direction 29 3.3.2 Left-hand direction 36 3.4 Time-optimal trajectory 42 3.5 Super-twisting sliding mode control 44 3.6 Computer simulation 46 3.6.1 Simulation 1 46 3.6.2 Simulation 2 47 3.6.3 Simulation 3 49 Chapter 4. Time-optimal trajectory for heaving motion control using buoyancy engine and propeller individually 51 4.1. Heave dynamics and TOT 51 4.2. Analytical solution of heave dynamics with buoyancy and thruster force individually 54 4.2.1 First segment with positive rate 54 4.2.2 Second segment with maximum input 55 4.2.3 Third segment with constant velocity 56 4.2.4 Fourth segment with negative rate 57 4.2.5 Fifth segment with minimum input 58 4.3. Time-optimal trajectory for depth motion 59 4.3.1 Find z1, w1 and w1 59 4.3.2 Find t2, z2, w2 and w2 61 4.3.3 Find w3, z4 and w4 62 4.3.4 Find z3, t3 and t4 63 4.3.5 Find α and t5 64 4.4. Sliding mode control for heave dynamics 64 4.5. Computer simulation 66 4.5.1. Simulation 1 66 4.5.2. Simulation 2 69 Chapter 5. Experimental study of direct adaptive control along TOT for heading motion 72 5.1. Motivation 72 5.2. Composition of RHUG 73 5.3. Robust adaptive control for heading dynamics 77 5.4. Computer simulation 79 5.5 Experiment 82 5.5.1 First experiment with k1=2.5,k2=30 82 5.5.2 Second experiment with k1=2,k2=30 83 5.5.3 Third experiment with k1=2,k2=50 85 Chapter 6. Robust adaptive control design for vertical motion 89 6.1. Dynamics of vertical plane 89 6.2. Adaptive sliding-mode control for pitch motion 91 6.3. Adaptive sliding-mode control for surge motion 93 6.4. LOS and PI depth-keeping guidance 95 6.5. Computer simulation 97 6.5.1 Simulation 1 97 6.5.2 Simulation 2 104 Chapter 7. Conclusion 111 Reference 113Docto

Robust data assimilation in river flow and stage estimation based on multiple imputation particle filter

In this paper, new method is proposed for a more robust Data Assimilation (DA) design of the river flow and stage estimation. By using the new sets of data that are derived from the incorporated Multi Imputation Particle Filter (MIPF) in the DA structure, the proposed method is found to have overcome the issue of missing observation data and contributed to a better estimation process. The convergence analysis of the MIPF is discussed and shows that the number of the particles and imputation influence the ability of this method to perform estimation. The simulation results of the MIPF demonstrated the superiority of the proposed approach when being compared to the Extended Kalman Filter (EKF) and Particle Filter (PF)

Robust Adaptive Depth Control of Hybrid Underwater Glider in Vertical Plane

Hybrid underwater glider (HUG) is an advanced autonomous underwater vehicle with propellers capable of sustainable operations for many months. Under the underwater disturbances and parameter uncertainties, it is difficult that the HUG coordinates with the desired depth in a robust manner. In this study, a robust adaptive control algorithm for the HUG is proposed. In the descend and ascend periods, the pitch control is designed using backstepping technique and direct adaptive control. When the vehicle approaches the target depth, the surge speed control using adaptive control combined with the pitch control is used to keep the vehicle at the desired depth with a constant cruising speed in the presence of the disturbances. The stability of the proposed controller is verified by using the Lyapunov theorem. Finally, the computer simulation using the numerical method is conducted to show the effectiveness of the proposed controller for a hybrid underwater glider system

Energy efficient navigational methods for autonomous underwater gliders in surface denied regions

Autonomous underwater gliders routinely perform long duration profiling missions while characterizing the chemical, physical and biological properties of the water column. These measurements have opened up new ways of observing the ocean’s processes and their interactions with the atmosphere across time and length scales which were not previously possible. Extending these observations to ice-covered regions is of importance due to their role in ocean circulation patterns, increased economic interest in these areas and a general sparsity of observations. This thesis develops an energy optimal depth controller, a terrain aided navigation method and a magnetic measurement method for an autonomous underwater glider. A review of existing methods suitable for navigation in underwater environments as well as the state of the art in magnetic measurement and calibration techniques is also presented. The energy optimal depth controller is developed and implemented based on an integral state feedback controller. A second order linear time invariant system is identified from field data and used to compute the state feedback controller gains through an augmented linear quadratic regulator. The resulting gains and state feedback controller methodology are verified through field trials and found to control the depth of the vehicle while losing less than one percent of the vehicle’s propulsive load to control inputs or lift induced drag. The terrain aided navigation method is developed based on a jittered bootstrap algorithm which is a type of particle filter that makes use of the vehicle’s deadreckoned navigation solution, onboard altimeter and a local digital parameter model (DPM). An evaluation is performed through post-processing offline location estimates from field trials which took place in Holyrood Arm, Newfoundland, overlapping a previously collected DPM. During the post-processing of these trials, the number of particles, jittering variance and DPM grid cell size were varied. Online open loop field trials were performed through integrating a new single board computer. In these trials the localization error remained bounded and improved on the dead reckoning error, validating the filter despite the large dead-reckoned errors, single beam altitude measurements, and short test duration. Terrain aided navigation methods perform poorly in regions of flat terrain or in deep water where the seafloor is beyond the range of the altimeter. Magnetic measurements of the Earth’s main field have been proposed previously to augment terrain aided navigation algorithms in these regions. To this end a low power magnetic instrumentation suite for an underwater glider has been developed. Two calibration methodologies were also developed and compared against regional digital models of the magnetic field. The calibration methods include one for which the actuators in the vehicle were kept in fixed locations and a second for which the calibration coefficients were parameterized for the actuator locations. Both methods were found to agree with the low frequency content in the a-priori regional magnetic anomaly grids

Design considerations for engineering autonomous underwater vehicles

Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2007Autonomous Underwater Vehicles (AUVs) have been established as a viable tool for Oceanographic Sciences. Being untethered and independent, AUVs fill the gap in Ocean Exploration left by the existing manned submersible and remotely operated vehicles (ROV) technology. AUVs are attractive as cheaper and efficient alternatives to the older technologies and are breaking new ground in many applications. Designing an autonomous vehicle to work in the harsh environment of the deep ocean comes with its set of challenges. This paper discusses how the current engineering technologies can be adapted to the design of AUVs. Recently, as the AUV technology has matured, we see AUVs being used in a variety of applications ranging from sub-surface sensing to sea-floor mapping. The design of the AUV, with its tight constraints, is very sensitive to the target application. Keeping this in mind, the goal of this thesis is to understand how some of the major issues affect the design of the AUV. This paper also addresses the mechanical and materials issues, power system design, computer architecture, navigation and communication systems, sensor considerations and long term docking aspects that affect AUV design. With time, as the engineering sciences progress, the AUV design will have to change in order to optimize its performance. Thus, the fundamental issues discussed in this paper can assist in meeting the challenge of maintaining AUV design on par with modern technology.This work was funded by the NSF Center for Subsurface Sensing and Imaging Systems (CenSSIS) Engineering Research Center (ENC) grant no. EEC-99868321

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

A future for intelligent autonomous ocean observing systems

Ocean scientists have dreamed of and recently started to realize an ocean observing revolution with autonomous observing platforms and sensors. Critical questions to be answered by such autonomous systems are where, when, and what to sample for optimal information, and how to optimally reach the sampling locations. Definitions, concepts, and progress towards answering these questions using quantitative predictions and fundamental principles are presented. Results in reachability and path planning, adaptive sampling, machine learning, and teaming machines with scientists are overviewed. The integrated use of differential equations and theory from varied disciplines is emphasized. The results provide an inference engine and knowledge base for expert autonomous observing systems. They are showcased using a set of recent at-sea campaigns and realistic simulations. Real-time experiments with identical autonomous underwater vehicles (AUVs) in the Buzzards Bay and Vineyard Sound region first show that our predicted time-optimal paths were faster than shortest distance paths. Deterministic and probabilistic reachability and path forecasts issued and validated for gliders and floats in the northern Arabian Sea are then presented. Novel Bayesian adaptive sampling for hypothesis testing and optimal learning are finally shown to forecast the observations most informative to estimate the accuracy of model formulations, the values of ecosystem parameters and dynamic fields, and the presence of Lagrangian Coherent Structures