Aerospace Engineering Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/2737

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DYNAMICS AND CONTROL OF AN ELASTIC ROD IN AIR AND WATER
(2019) Burch, Travis Taylor; Paley, Derek A; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This thesis investigates the modeling and control of bio-inspired flexible structures for robotics applications. Many animals move through complicated natural environments and perform complex tasks by exploiting soft structures. Soft structures are highly versatile and are a growing area of interest in robotics because they can have decreased weight, size, and mechanical complexity relative to more traditional rigid robotics. This work uses planar discrete elastic rod (PDER) theory for modeling two types of flexible structures. First, a flexible airfoil is modeled using PDER theory, including the Improved Lighthill model (ILM) of hydrodynamic forces to study the propulsion thrust. The propulsion thrust generated by rigid and flexible foils are also measured experimentally and compared to the model. Second, a state-space description of a flexible pendulum with torque input is presented. Linear state-and output-feedback hybrid controllers stabilize the inverted flexible pendulum starting from the down equilibrium.
Bioinspired sensing and control for underwater pursuit
(2019) Free, Brian Anderson; Paley, Derek A; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Fish in nature have several distinct advantages over traditional propeller driven underwater vehicles including maneuverability and flow sensing capabilities. Taking inspiration from biology, this work seeks to answer three questions related to bioinspired pursuit and apply the knowledge gained therein to the control of a novel, reaction-wheel driven autonomous fish robot. Which factors are most important to a successful pursuit? How might we guarantee capture with underwater pursuit? How might we track the wake of a flapping fish or vehicle? A technique called probabilistic analytical modeling (PAM) is developed and illustrated by the interactions between predator and prey fish in two case studies that draw on recent experiments. The technique provides a method for investigators to analyze kinematics time series of pursuit to determine which parameters (e.g. speed, flush distance, and escape angles) have the greatest impact on metrics such as probability of survival. Providing theoretical guarantees of capture become complicated in the case of a swimming fish or bioinspired fish robot because of the oscillatory nature fish motion. A feedback control law is shown to result in forward swimming motion in a desired direction. Analysis of this law in a pursuit scenario yields a condition stating whether capture is guaranteed provided some basic information about the motion of the prey. To address wake tracking inspiration is taken from the lateral line sensing organ in fish, which is sensitive to hydrodynamic forces in the local flow field. In experiment, an array of pressure sensors on a Joukowski foil estimates and controls flow-relative position in a Karman vortex street using potential flow theory, recursive Bayesian filtering, and trajectory-tracking, feedback control. The work in this dissertation pushes the state of the art in bioinspired underwater vehicles closer to what can be found in nature. A modeling technique provides a means to determine what is most important to pursuit when designing a vehicle, analysis of a control law shows that a robotic fish is capable of pursuit engagements with capture guarantees, and an estimation framework demonstrates how the wake of a swimming fish or obstacle in the flow can be tracked.
Expanding Constrained Kinodynamic Path Planning Solutions through Recurrent Neural Networks
(2019) Shaffer, Joshua Allen; Xu, Huan; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Path planning for autonomous systems with the inclusion of environment and kinematic/dynamic constraints encompasses a broad range of methodologies, often providing trade-offs between computation speed and variety/types of constraints satisfied. Therefore, an approach that can incorporate full kinematics/dynamics and environment constraints alongside greater computation speeds is of great interest. This thesis explores a methodology for using a slower-speed, robust kinematic/dynamic path planner for generating state path solutions, from which a recurrent neural network is trained upon. This path planning recurrent neural network is then used to generate state paths that a path-tracking controller can follow, trending the desired optimal solution. Improvements are made to the use of a kinodynamic rapidly-exploring random tree and a whole-path reinforcement training scheme for use in the methodology. Applications to 3 scenarios, including obstacle avoidance with 2D dynamics, 10-agent synchronized rendezvous with 2D dynamics, and a fully actuated double pendulum, illustrate the desired performance of the methodology while also pointing out the need for stronger training and amounts of training data. Last, a bounded set propagation algorithm is improved to provide the initial steps for formally verifying state paths produced by the path planning recurrent neural network.
SOFT ROBOTIC APPENDAGES USING PNEUMATIC ARTIFICIAL MUSCLES
(2018) Pillsbury, Thomas; Wereley, Norman M; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation focuses on advancing the state of the art in soft robotics using pneumatic artificial (PAM) actuators. Pneumatic artificial muscles are currently used in robotic and prosthetic applications due to their high power to weight ratio, controllable compliance, and simple design. Contractile PAMs are typically used in traditional hard robotics in place of heavy electric motors. As the field of soft robotics grows, extensile PAMs are beginning to have increased usage. The bladder of a PAM affects common actuator performance metrics, specifically: blocked force, free contraction, hysteresis, and dead-band pressure. This work investigates the effect that bladder thickness has on static actuation performance of small scale PAMs. Miniature PAMs were fabricated with a range of bladder thicknesses then experimentally characterized in quasi-static conditions, where results showed that increasing bladder wall thickness decreases blocked force and free contraction, while the dead-band pressure increases. A nonlinear model was then applied to determine the structure of the stress-strain relationship that enables accurate modeling and the minimum number of terms. Contractile and extensile PAMs were experimentally fabricated and parametrically compared to demonstrate the advantages and disadvantages of each type of PAM and applications for which they are best suited. An additional PAM model was developed based on finite strain theory to address the lack of predicitive models. The closed-form pneumatic artificial muscle quasi-static actuator force is obtained. The analysis was experimentally validated using actuation force versus contraction ratio test data at a series of discrete inflation pressures for four different pneumatic artificial muscles, two contractile and two extensile. This work investigates adding bio-inspired ossicle structures from brittle stars to pneumatic artificial muscle continuum arm sections. The ossicle structure increases the range of motion and load capability of the continuum arm section while reducing the pneumatic pressure requirements. In this work, a static model of the continuum arm section is developed assuming constant curvature in the section and finding the center of mass of the section and its end plate. This model is validated by comparing the pressure-angle relationship at various loading conditions.
TASK-BASED OPTIMIZATION OF MULTI-ARM SPACE ROBOTICS
(2018) McBryan, Katherine Marie; Akin, David L; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
There are many benefits to using multi-arm systems over a single arm system including higher flexibility in planning, better payload handling capacity, and reduction of joint torques. However, multi-arm systems are inherently more complex. This complexity does not necessarily translate to ``bigger" and ``heavier". This research seeks to answer the question of whether or not a multi-arm system can have lower mass than a single arm system. Using a task-based methodology, Independent single-arm and cooperative dual-arm manipulator systems are designed. A task defines the payload's motion and thus the manipulator's trajectory. Utilizing linear programming, a new method is developed in order to optimize the distribution of forces among the multiple arms in order to guarantee a minimum system mass. The mass of the motors and gears are estimated based on the required torque and speed, obtained from the trajectory and force-distribution. This study shows that a well-designed multi-arm system can in fact have a lower mass than a single-arm system. Further optimization demonstrates that a multi-arm system, when designed as a complete system rather than individual parts, can significantly reduce the total system mass.
CHARACTERIZING THE QUASI-STATIC AND DYNAMIC RESPONSE OF A NON-CONTACT MAGNETO-ELASTIC TORQUE SENSOR
(2017) Muller, Brooks Richard; Flatau, Alison; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Advances in the development of rolled-sheet magnetostrictive materials led to testing of a prototype wireless magneto-elastic torque (WiMET) sensor using the iron alloy Galfenol. As torque was applied to a shaft, stress-induced changes in the magnetic state of Galfenol that was bonded to the shaft were proportional to the applied torque. Building on that work, this thesis investigates strategies to improve both repeatability and the signal to noise ratio of WiMET sensor output. Multi-physics models of WiMET stress and magnetic states under applied torques are used to improve understanding of sensor operation. Testing to validate simulations is performed using Galfenol and Alfenol, a newer rolled-sheet alloy, for torsional loads of 0 – 200 in-lb, and under quasi-static and dynamic (0 – 2000 RPM) loading conditions. The experimental results presented support the potential of WiMET sensor use for dynamic torque measurement and health monitoring of drive train systems.
Wave impedance selection for passivity-based bilateral teleoperation
(2016) D'Amore, Nicholas; Akin, David L; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
When a task must be executed in a remote or dangerous environment, teleoperation systems may be employed to extend the influence of the human operator. In the case of manipulation tasks, haptic feedback of the forces experienced by the remote (slave) system is often highly useful in improving an operator's ability to perform effectively. In many of these cases (especially teleoperation over the internet and ground-to-space teleoperation), substantial communication latency exists in the control loop and has the strong tendency to cause instability of the system. The first viable solution to this problem in the literature was based on a scattering/wave transformation from transmission line theory. This wave transformation requires the designer to select a wave impedance parameter appropriate to the teleoperation system. It is widely recognized that a small value of wave impedance is well suited to free motion and a large value is preferable for contact tasks. Beyond this basic observation, however, very little guidance exists in the literature regarding the selection of an appropriate value. Moreover, prior research on impedance selection generally fails to account for the fact that in any realistic contact task there will simultaneously exist contact considerations (perpendicular to the surface of contact) and quasi-free-motion considerations (parallel to the surface of contact). The primary contribution of the present work is to introduce an approximate linearized optimum for the choice of wave impedance and to apply this quasi-optimal choice to the Cartesian reality of such a contact task, in which it cannot be expected that a given joint will be either perfectly normal to or perfectly parallel to the motion constraint. The proposed scheme selects a wave impedance matrix that is appropriate to the conditions encountered by the manipulator. This choice may be implemented as a static wave impedance value or as a time-varying choice updated according to the instantaneous conditions encountered. A Lyapunov-like analysis is presented demonstrating that time variation in wave impedance will not violate the passivity of the system. Experimental trials, both in simulation and on a haptic feedback device, are presented validating the technique. Consideration is also given to the case of an uncertain environment, in which an a priori impedance choice may not be possible.
Development of a Real-Time Hierarchical 3D Path Planning Algorithm for Unmanned Aerial Vehicles
(2016) Solomon, Matthew David; Xu, Huan; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Unmanned aerial vehicles (UAVs) frequently operate in partially or entirely unknown environments. As the vehicle traverses the environment and detects new obstacles, rapid path replanning is essential to avoid collisions. This thesis presents a new algorithm called Hierarchical D* Lite (HD*), which combines the incremental algorithm D* Lite with a novel hierarchical path planning approach to replan paths sufficiently fast for real-time operation. Unlike current hierarchical planning algorithms, HD* does not require map corrections before planning a new path. Directional cost scale factors, path smoothing, and Catmull-Rom splines are used to ensure the resulting paths are feasible. HD* sacrifices optimality for real-time performance. Its computation time and path quality are dependent on the map size, obstacle density, sensor range, and any restrictions on planning time. For the most complex scenarios tested, HD* found paths within 10% of optimal in under 35 milliseconds.
Bio-Inspired Small Field Perception for Navigation and Localization of MAV's in Cluttered Environments
(2015) Escobar-Alvarez, Hector Domingo; Humbert, Sean J; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Insects are capable of agile pursuit of small targets while flying in complex cluttered environments. Additionally, insects are able to discern a moving background from smaller targets by combining their lightweight and fast vision system with efficient algorithms occurring in their neurons. On the other hand, engineering systems lack such capabilities since they either require large sensors, complex computations, or both. Bio-inspired small-field perception mechanisms have the potential to enhance the navigation of small unmanned aircraft systems in cluttered unknown environments. In this dissertation, we propose and investigate three methods to extract information about small-field objects from optic flow. The first method, \textit{flow of flow}, is analogous to processes taking place at the medulla level of the fruit-fly visuomotor system. The two other methods proposed are engineering approaches analogous to the figure-detection sensitive neurons at the lobula. All three methods employed demonstrated effective small-field information extraction from optic flow. The methods extract relative distance and azimuth location to the obstacles from an optic flow model. This optic flow model is based on parameterization of an environment containing small and wide-field obstacles. The three methodologies extract the high spatial frequency content of the optic flow by means of an elementary motion detector, Fourier series, and wavelet transforms, respectively. This extracted signal will contain the information about the small-field obstacles. The three methods were implemented on-board both a ground vehicle and an aerial vehicle to demonstrate and validate obstacle avoidance navigation in cluttered environments. Lastly, a localization framework based on wide field integration of nearness information (inverse of depth) is used for estimating vehicle navigation states in an unknown environment. Simulation of the localization framework demonstrates the ability to navigate to a target position using only nearness information.
HEIGHT ESTIMATION AND CONTROL OF A ROTORCRAFT IN GROUND EFFECT USING MULTIPLE PRESSURE PROBES
(2015) Hooi, Chin Gian; Paley, Derek A; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This thesis describes a dynamic height estimator and controller for rotorcraft landing and hovering in ground effect based on flowfield sensing and modeling. The rotor downwash in ground effect is represented using a ring-source potential flow model selected for real-time use. Experimental verification of the flow model and an augmented flow model for tilt are presented. A nonlinear dynamic model of a compound pendulum heave test stand that reduces to the dynamics of a rotorcraft in ground effect is presented with open-loop analysis and closed-loop control simulation. Equations of motion and stability characterization of of a heaving rotor IGE are derived for external perturbations and it is shown that a uniform sideward wind does not cause instability and uniform axial wind from the top can cause instability. Flowfield velocity measurements are assimilated into a grid-based recursive Bayesian filter to estimate height above ground in both simulation and experiment. Height tracking in ground effect and landing using the estimated height are implemented with a dynamic linear controller in both simulation and experiment. Mean estimation and motion errors are found to be no greater than 5% and 9% respectively, demonstrating that height estimation and control is possible with only flow sensing and modeling.

Aerospace Engineering Theses and Dissertations

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