Transformations/Constraints of UAV with Dynamic Modelling

Unmanned Aerial Vehicles (UAVs) have automated, monitored in real time, and collected data in a manner most industries had never seen before. This paper will delve into UAV advancements, challenges, and its applications. Furthermore, the focus is on machine learning and self-contained navigation systems on UAVs. For this purpose, the simulation models the UAV dynamics using the Newton-Euler equations with PID controllers, developed in MATLAB. The model captures the roll, pitch, and yaw motions of the UAV in flight to the degree necessary for the analysis to be useful. The analysis validates the developed model and provides the groundwork for further research on the flight behavior of UAVs under different conditions. With the exception of battery life and regulatory hurdles, the advancements in artificial intelligence and control systems will make UAVs more versatile for use in smart cities, defense, and industrial applications.