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
Cite This Article
SCIEPublish Style
Munasinghe SR. A Quadrotor Simulation and Research Platform. Drones and Autonomous Vehicles2025, 2, 10014. https://doi.org/10.70322/dav.2025.10014
AMA Style
Munasinghe SR. A Quadrotor Simulation and Research Platform. Drones and Autonomous Vehicles. 2025; 2(3):10014. https://doi.org/10.70322/dav.2025.10014