Session: ASME Undergraduate Student Design Expo

Paper Number: 175896

Retractable Tether Multirotor Uav 

Multirotor unmanned aerial vehicles (MUAVs) have emerged as highly adaptable and cost-effective platforms for missions such as payload transportation, environmental monitoring, and search and rescue. A tethered MUAV (TMUAV), equipped with a tether connected to the vehicle, extends this capability by enabling sensor deployment while hovering above hazardous or inaccessible terrains, including disaster zones and urban structures. However, the introduction of a tether significantly complicates system modeling and controller design. Unlike a rigid link, a tether alternates between slack and taut states, each governed by distinct dynamics. Transitions between these states introduce impulsive dynamics that can destabilize the vehicle, especially under external disturbances such as wind gusts or obstacle contact. Accurate simulation and reliable control therefore require not only capturing both tether regimes but also modeling their transitions smoothly. Although the existing literature emphasizes the slack–taut distinction, it generally lacks a unified framework capable of robustly handling these transitions. This project addresses this gap by developing a robust, adaptive control framework and simulation environment that capture realistic tether dynamics, with a particular focus on nonlinear behaviors during slack–taut transitions. The objective is to enable stable and reliable operation of TMUAVs in dynamic environments. 

The simulation environment was implemented in MATLAB using dynamic models adapted from prior work to represent both slack and taut tether conditions. The MUAV and payload were initialized at ground level with the tether in the slack state. Transitions between slack and taut were determined by two conditions: (1) the relative distance between the MUAV and payload compared to the tether length, and (2) the tension in the tether. In the slack state, the controller monitored MUAV–payload separation to predict whether tautness would occur in the next iteration. In the taut state, the controller evaluated cable tension and reverted to the slack model if the tension dropped below a threshold. To further mitigate unnecessary slack–taut transitions after liftoff, a minimum-jerk trajectory was generated and tested, providing a stable baseline and a benchmark against which non-minimum-jerk trajectories could be evaluated. 

With this foundation, the framework was extended to simulate non-optimized trajectories. While minimum-jerk trajectories offer stability, they fail to fully capture the operational demands of real-world missions. In practice, MUAVs carrying suspended payloads may be required to execute aggressive maneuvers with high jerk, such as sharp turns, rapid accelerations, or abrupt path changes in cluttered or time-critical environments. These scenarios impose greater stress on the tether, intensify slack–taut transitions, and reveal nonlinear dynamics that smooth trajectories conceal. By simulating and analyzing such aggressive maneuvers, this project evaluates the robustness of the proposed framework under worst-case operating conditions, with the goal of ensuring reliable TMUAV control even when the vehicle must perform beyond idealized smooth paths. 

Presenting Author: Shashwat Yadav University of South Carolina

Presenting Author Biography: Shashwat Yadav is an Aerospace Engineering student in the University of South Carolina Honors College, maintaining a 4.0 GPA and pursuing a passion for aerospace vehicles and applied research. His experience spans projects such as stabilizing quadrotor UAVs with retractable tether systems, investigating soot removal methods in diesel particulate filters, and studying the effects of nanoparticles on soil health—work that earned recognition at the South Carolina Junior Academy of Science. He has developed strong technical skills in CAD modeling, CFD analysis, programming, and 3D fabrication, applying these tools to both academic research and practical engineering challenges. Beyond the classroom, he is the Aerodynamics Team Lead for the Society of Automotive Engineers, where he applies computational fluid dynamics and wind tunnel testing to optimize Formula SAE designs. He is also an active member of Hands On Prosthetic Engineering and the American Institute of Aeronautics and Astronautics, contributing CAD designs and collaborating on hands-on engineering projects. With a foundation in leadership, research, and technical problem-solving, he is eager to continue growing his expertise while contributing meaningfully to the fields of aerospace and mechanical engineering.

Authors:

Shashwat Yadav University of South Carolina
Dario Handrick University of South Carolina
Junsoo Lee University of South Carolina