Mathematics Senior Capstone Papers

Document Type

Article

Publication Date

Spring 2024

Abstract

Uncrewed Aerial Vehicles (UAVs) are a prevalent technology in many fields. They must be lightweight, efficient, and stable in order to carry out their objectives or support a payload. The control system that maintains a UAV’s attitude directly contributes to the stability and efficiency of the UAV, and more efficient UAVs can be made more lightweight by reducing battery size. Because the UAV has only four degrees of control (one per motor) but requires twelve dimensions to describe its orientation and position over time, it is considered an under-actuated nonlinear complex system. In this study, we compare various linear control systems and implementations in a simulated environment with MATLAB to inform engineers of the relevant benefits and trade-offs of each approach. The control systems studied were the Proportional- Integral-Derivative controller (PID), the Linear Quadratic Gaussian controller (LQG), the Model-Predictive controller (MPC), and the Feedback Linearization Controller (FLC). The UAV kinematics were modeled in MATLAB. For each control algorithm, we bench-marked the code performance and ran the most intensive controllers at lower update frequencies to provide a fair comparison assuming comparable hardware. We primarily considered how long a controller took to initially reach its desired state (rise time), how much a controller overshot its target state (overshoot), and how long a controller took to stabilize at its target state (settling time).

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