Date of Award
2025
Document Type
Open Access Dissertation
Department
Electrical Engineering
First Advisor
Xiaofeng Wang
Abstract
Multirotor aerial vehicles (MAVs) have seen explosive popularity since the early 2000s, with microprocessors enabling small-scale Autonomous Aerial Vehicles (AAVs) or First Person Aerial Vehicles (FPVs). Additionally, the use of these MAVs in commercial applications has continued to grow since then with expansion into delivery, search and rescue, and smart farming applications. With this rise in popularity, specialized MAVs have undergone development for these applications due to the environments in which these vehicles operate.
From this development, a new area of Morphological Multirotor Aerial Vehicles (MMAVs) has emerged. Unlike traditional MAVs, these platforms adjust their shape based on environmental factors. However, the addition of actuators to enable shape changing, known as morphology, requires more complex control algorithms.
In this dissertation, we aim to implement Model Predictive Control (MPC) structures within existing control architectures for these commercial applications, enabling robust and stable flight characteristics in several key morphologies.
First, a telescoping MAV uses prismatic actuators to extend and retract the propeller positions along the support arms. This morphing capability enables a greater range in the position of the center of mass in delivery applications where uncertainties in the payload may exist.
Second, a folding MAV uses rotational actuators to fold the support arms for the propellers, allowing for varying shape changes. Again, this morphing capability can enable a greater range of motion for the center of mass. Where current applications focus on stabilizing specific shapes, we instead morph the drone to enhance the stability envelope.
Finally, by combining both the folding and telescoping morphologies, it is possible to configure a quadrotor into a trirotor if a propeller breaks or a motor fails. Traditional techniques have been unable to stabilize the system in this configuration due to complexities. However, our approach, demonstrated through comprehensive simulated experiments, will show its effectiveness over these traditional techniques.
Rights
© 2025, Samuel Allen Dauchert
Recommended Citation
Dauchert, S. A.(2025). Multirotor Aerial Vehicle Morphology Design, Modeling, And Control. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/8714