Controls and Control Theory Commons^™

Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt

All Dissertations

Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …

Cyber-Threat Detection Strategies Governed By An Observer And A Neural-Network For An Autonomous Electric Vehicle, Douglas Scruggs

All Theses

A pathway to prevalence for autonomous electrified transportation is reliant upon accurate and reliable information in the vehicle’s sensor data. This thesis provides insight as to the effective cyber-attack placements on an autonomous electric vehicle’s lateral stability control system (LSCS). Here, Data Integrity Attacks, Replay Attacks, and Denial-of-Service attacks are placed on the sensor data describing the vehicle’s actual yaw-rate and sideslip angle. In this study, there are three different forms of detection methods. These detection methods utilize a residual metric that incorporate sensor data, a state-space observer, and a Neural-Network. The vehicle at hand is a four-motor drive autonomous …

Safe Navigation Of Quadruped Robots Using Density Functions, Andrew Zheng

All Theses

Safe navigation of mission-critical systems is of utmost importance in many modern autonomous applications. Over the past decades, the approach to the problem has consisted of using probabilistic methods, such as sample-based planners, to generate feasible, safe solutions to the navigation problem. However, these methods use iterative safety checks to guarantee the safety of the system, which can become quite complex. The navigation problem can also be solved in feedback form using potential field methods. Navigation function, a class of potential field methods, is an analytical control design to give almost everywhere convergence properties, but under certain topological constraints and …

Improved Vehicle-Bridge Interaction Modeling And Automation Of Bridge System Identification Techniques, Omar Abuodeh

All Dissertations

The Federal Highway Administration (FHWA) recognizes the necessity for cost-effective and practical system identification (SI) techniques within structural health monitoring (SHM) frameworks for asset management applications. Indirect health monitoring (IHM), a promising SHM approach, utilizes accelerometer-equipped vehicles to measure bridge modal properties (e.g., natural frequencies, damping ratios, mode shapes) through bridge vibration data to assess the bridge's condition. However, engineers and researchers often encounter noise from road roughness, environmental factors, and vehicular components in collected vehicle signals. This noise contaminates the vehicle signal with spurious modes corresponding to stochastic frequencies, impacting damage monitoring assessments. Thus, an efficient and reliable SI …

The Application Of Model Predictive Control On Paralleled Converters For Zero Sequence Current Suppression And Active Thermal Management, Justin Dobey

All Theses

In the field of power electronics, the control of rectifiers is a crucial area of study. Rectifiers are used to convert AC power into DC power, and are commonly used in a wide range of applications, including renewable energy systems, industrial automation, and consumer electronics. However, in medium and high-power systems when multiple rectifiers are connected in parallel to a DC bus, stability issues can arise, including voltage fluctuations, zero sequence circulating current, and thermal imbalance.

Achieving stable DC bus voltage is essential for maintaining the proper functioning of electronic devices, while suppressing zero sequence current is necessary for protecting …

Deep Reinforcement Learning And Game Theoretic Monte Carlo Decision Process For Safe And Efficient Lane Change Maneuver And Speed Management, Shahab Karimi

All Dissertations

Predicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communication and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. This dissertation presents a decision process model for real-time automated lane change and speed management in highway and urban traffic. In lane change and merge maneuvers, it is important to know how neighboring vehicles will act in the imminent future. Human driver …