von Ellenrieder, Karl

Towing tank/water flume experiments are conducted to characterize the dynamics
of a Remotely-Piloted Unmanned Underwater Vehicle (RPUUV) propelled by a
vectored-thruster system. Force and torque measurements are used to determine the
coefficients of drag, lift, yaw-moment and thrust of the vehicle as a function of the
vehicle yaw angle and the vectored-thruster rudder angle. Simultaneously, particle Image
Velocimetry (PIV) measurements of the propeller inlet flow are also performed to
examine the variation of flow conditions at the propeller inlet with rudder angle. The tests
are conducted at 0.150 rnls, 0.300 rnls, 0.515 rnls and 0.773 rnls. While the measured
drag coefficient is slightly higher than predicted by theory at low Reynolds number (1.44
x10^5 and 2.88 x10^5), the hydrodynamic coefficients data are expected to be useful in
predicting the response of vehicles in the field. Additionally, the magnitude of the thrust
vector varies nonlinearly with rudder angle and for nonzero rudder angles the thrust
vector does not point in the same direction as the thruster axis.

novel approach to extend the decision-making capabilities of unmanned surface vehicles
(USVs) is presented in this work. A multi-objective framework is described where separate
controllers command different behaviors according to a desired trajectory. Three behaviors
are examined – transiting, station-keeping and reversing. Given the desired trajectory, the
vehicle is able to autonomously recognize which behavior best suits a portion of the
trajectory. The USV uses a combination of a supervisory switching control structure and a
reinforcement learning algorithm to create a hybrid deliberative and reactive approach to
switch between controllers and actions. Reinforcement learning provides a deliberative
method to create a controller switching policy, while supervisory switching control acts
reactively to instantaneous changes in the environment. Each action is restricted to one
controller. Due to the nonlinear effects in these behaviors, two underactuated backstepping
controllers and a fully-actuated backstepping controller are proposed for each transiting, reversing and station-keeping behavior, respectively, restricted to three degrees of freedom.
Field experiments are presented to validate this system on the water with a physical USV
platform under Sea State 1 conditions. Main outcomes of this work are that the proposed
system provides better performance than a comparable gain-scheduled nonlinear controller
in terms of an Integral of Absolute Error metric. Additionally, the deliberative component
allows the system to identify dynamically infeasible trajectories and properly
accommodate them.

In this research, a wind feedforward (FF) controller has been developed to augment closed loop feedback controllers for the position and heading station keeping control of Unmanned Surface Vehicles (USVs). The performance of the controllers was experimentally tested using a 16 foot USV in an outdoor marine environment. The FF controller was combined with three nonlinear feedback controllers, a Proportional–Derivative (PD) controller, a Backstepping (BS) controller, and a Sliding mode (SM) controller, to improve the station-keeping performance of the USV. To address the problem of wind model uncertainties, adaptive wind feedforward (AFF) control schemes are also applied to the FF controller, and implemented together with the BS and SM feedback controllers. The adaptive law is derived using Lyapunov Theory to ensure stability. On-water station keeping tests of each combination of FF and feedback controllers were conducted in the U.S. Intracoastal Waterway in Dania Beach, FL USA. Five runs of each test condition were performed; each run lasted at least 10 minutes. The experiments were conducted in Sea State 1 with an average wind speed of between 1 to 4 meters per second and significant wave heights of less than 0.2 meters. When the performance of the controllers is compared using the Integral of the Absolute Error (IAE) of position criterion, the experimental results indicate that the BS and SM feedback controllers significantly outperform the PD feedback controller (e.g. a 33% and a 44% decreases in the IAE, respectively). It is also found that FF is beneficial for all three feedback controllers and that AFF can further improve the station keeping performance. For example, a BS feedback control combined with AFF control reduces the IAE by 25% when compared with a BS feedback controller combined with a non-adaptive FF controller. Among the eight combinations of controllers tested, SM feedback control combined with AFF control gives the best station keeping performance with an average position and heading error of 0.32 meters and 4.76 degrees, respectively.

Numerical simulations of waterjet inlets have been conducted in order to understand inlet performance during ship turning maneuvers. During turning maneuvers waterjet systems may experience low efficiency, cavitation, vibration, and noise. This study found that during turns less energy arrived at the waterjet pump relative to operating straight ahead, and that the flow field at the entrance of the waterjet pump exhibited a region of both low pressure and low axial velocity. The primary reason for the change in pump inflow uniformity is due to a streamwise vortex. In oblique inflow the hull boundary layer separates when entering the inlet and wraps up forming the streamwise vortex. These changes in pump inflow during turning maneuvers will result in increased unsteady loading of the pump rotor and early onset of pump rotor cavitation.

Options for tracking dynamic underwater targets using optical methods is currently limited. This thesis examines optical reflectance intensities utilizing Lambert’s Reflection Model and based on a proposed underwater laser tracking system. Numerical analysis is performed through simulation to determine the detectable light intensities based on relationships between varying inputs such as angle of illumination and target position. Attenuation, noise, and laser beam spreading are included in the analysis. Simulation results suggest optical tracking exhibits complex relationships based on target location and illumination angle. Signal to Noise Ratios are a better indicator of system capabilities than received intensities. Signal reception does not necessarily confirm target capture in a multi-sensor network.

A motion compensated ADV system was evaluated to determine its ability to
make measurements necessary for characterizing the variability of the ambient current in
the Gulf Stream. The impact of IMU error relative to predicted turbulence spectra was
quantified, as well as and the ability of the motion compensation approach to remove
sensor motion from the ADV measurements. The presented data processing techniques
are shown to allow the evaluated ADV to be effectively utilized for quantifying ambient
current fluctuations from 0.02 to 1 Hz (50 to 1 seconds) for dissipation rates as low as
3x10-7. This measurement range is limited on the low frequency end by IMU error,
primarily by the calculated transformation matrix, and on the high end by Doppler noise.
Inshore testing has revealed a 0.37 Hz oscillation inherent in the towfish designed and
manufactured as part of this project, which can nearly be removed using the IMU.

The design and validation of a low-level backstepping controller for speed and
heading that is adaptive in speed for a twin-hulled underactuated unmanned surface
vessel is presented. Consideration is given to the autonomous launch and recovery of an
underwater vehicle in the decision to pursue an adaptive control approach. Basic system
identification is conducted and numerical simulation of the vessel is developed and
validated. A speed and heading controller derived using the backstepping method and a
model reference adaptive controller are developed and ultimately compared through
experimental testing against a previously developed control law. Experimental tests show
that the adaptive speed control law outperforms the non-adaptive alternatives by as much
as 98% in some cases; however heading control is slightly sacrificed when using the
adaptive speed approach. It is found that the adaptive control law is the best alternative
when drag and mass properties of the vessel are time-varying and uncertain.

The relationship between cross-flow at a waterjet inlet and delivered thrust is not
fully understood. A direct thrust measurement system was designed for a waterjet
propelled, free running USV. To induce sway velocity at the waterjet inlet, which was
considered equivalent to the cross flow, circles of varying radii were performed at
Reynolds Numbers between 3.48 x 106 and 8.7 x 106 and radii from 2.7 to 6.3 boat
lengths. Sway velocities were less than twenty percent of mean forward speed with slip
angles that were less than 20°. Thrust Loading Coefficients were compared to sway as
a percent of forward speed. In small radius turns, no relationship was seen, while in
larger radius turns, peaks of sway velocity corresponded with drops in thrust, but this
was determined to be caused by reduced vehicle yaw in these intervals . Decoupling of
thrust and yaw rate is recommended for future research.

Particle image velocimetry and flow visualization are used to characterize the wake of a heaving airfoil in a set of two experiments. In the first experiment a tandem airfoil configuration is used, with a stationary airfoil downstream of a heaving airfoil (modified Schmidt wave-propeller). Several vortex structures are identified for a forced Strouhal number (St)---based on airfoil chord-length, forcing frequency, and free-steam velocity---for 0.1 < St < 0.7. An asymmetric average velocity profile is measured in the upper St range. In the second experiment, the wake behind a single heaving airfoil is further inspected, with the purpose of highlighting the asymmetric wake, for 0.1 < St < 1.0. A maximum wake excursion of 18 degrees is measured at St = 0.6, and a minimum excursion of 5.7 degrees occurs at St = 0.9. Using averaged velocity profiles, a virtual origin of the wake excursion is also calculated.