In the master's thesis, we modeled and controlled a quadcopter using the LQR method in the
Simulink software environment. The quadcopter model was linearized around the hovering
point and represented in state space, then the gain matrix K for the linear model was
determined using the LQR method. The same approach was applied to the nonlinear model.
Both models were analyzed in terms of step response. In the nonlinear model, we compared
the system response using the LQR method and the PID controller. Control included
rotations around the x, y, and z axes and translation in the z – direction. Additionally, we
identified key parameters for modeling the quadcopter using a data acquisition system. We
found that the LQR method, designed for linear models, also works on nonlinear models and
provides a response without overshoot compared to the PID controller.
|