A Quadrotor Simulation and Research Platform

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A Quadrotor Simulation and Research Platform

Author Information
1
College of Agriculture and Life Sciences, Cornell University, Ithaca, NY 18450, USA
2
Department of IT and Entrepreneurship, Narva College, Tartu University, 50090 Tartu, Estonia
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Received: 10 April 2025 Accepted: 01 August 2025 Published: 17 September 2025

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© 2025 The authors. This is an open access article under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

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Drones Veh. Auton. 2025, 2(3), 10014; DOI: 10.70322/dav.2025.10014
ABSTRACT: The quadrotor is an underactuated, nonlinear system that presents significant challenges in both modeling and control design. This work develops a decoupled control framework based on the translational (Newtonian) and rotational (Eulerian) dynamics of the quadrotor. A Linear Quadratic Gaussian (LQG) regulator is implemented for control, with two extended Kalman filters employed for state estimation in the respective dynamic subsystems. The full design process, from dynamic modeling to flight simulation presented in detail. Key elements include nonlinear simulation, model linearization, state-space representation, feedforward compensation, Linear Quadratic Regulator (LQR) gain tuning, actuator dynamics, sensor noise, LQG design, and extended Kalman filter. The limitations of applying linear control to a nonlinear system are also presented.
Keywords: Quadrotor dynamic modeling; Mechanics and control of quadrotor; Sensor-based quadrotor control; Linear quadratic regulator; Extended kalman filter
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