Author Information

Is this project an undergraduate, graduate, or faculty project?

Undergraduate

Project Type

individual

Campus

Daytona Beach

Authors' Class Standing

Diya Patil, Freshman

Lead Presenter's Name

Diya Patil

Lead Presenter's College

DB College of Engineering

Faculty Mentor Name

Dr. Ronald Adams

Abstract

3 & 4 motor systems have been in the world of aviation in many different forms as the field grows and evolves. To understand the complexities of an Unmanned Aerial Vehicle (UAV) and its stability, assessing the amount of thrust put into each motor can help generate the torque produced despite factors such as multidirectional movement. While a UAV does this multiple times a second, producing a simplified version of this calculation can aid in simpler models simulating UAV movement. Due to the popularity of the quadcopter drone, a simple algorithm depicting thrust through each spinning motor can aid in teaching stability through linear systems. In this scenario, a 4 x 4 matrix was used to take the ideal total thrust inputted by the user, as well as roll, pitch, and yaw torque, to be able to get the motor thrusts. Additionally, the algorithm can take the specificities of the drone model, such as the arm length and yaw coefficient. Using these inputs, the algorithm can run a LU-decomposition to be able to determine how much thrust each motor should produce. Using this model, individual thrusts are easier to visualize, making calculations for thrusts simpler. Overall, LU-decomposition can aid in a multitude of different applications in the context of UAVs; however, this model makes its usage simple and digestible, making it a tool for quick hypotheticals and possible educational purposes.

Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?

No

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Modelling Quadcopter Thrust and Torque Using LU-Decomposition

3 & 4 motor systems have been in the world of aviation in many different forms as the field grows and evolves. To understand the complexities of an Unmanned Aerial Vehicle (UAV) and its stability, assessing the amount of thrust put into each motor can help generate the torque produced despite factors such as multidirectional movement. While a UAV does this multiple times a second, producing a simplified version of this calculation can aid in simpler models simulating UAV movement. Due to the popularity of the quadcopter drone, a simple algorithm depicting thrust through each spinning motor can aid in teaching stability through linear systems. In this scenario, a 4 x 4 matrix was used to take the ideal total thrust inputted by the user, as well as roll, pitch, and yaw torque, to be able to get the motor thrusts. Additionally, the algorithm can take the specificities of the drone model, such as the arm length and yaw coefficient. Using these inputs, the algorithm can run a LU-decomposition to be able to determine how much thrust each motor should produce. Using this model, individual thrusts are easier to visualize, making calculations for thrusts simpler. Overall, LU-decomposition can aid in a multitude of different applications in the context of UAVs; however, this model makes its usage simple and digestible, making it a tool for quick hypotheticals and possible educational purposes.

 

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