Localization and Trajectory Control Algorithms Applied on Drones - Brito, Alexandre Filipe Zambujo de (2019)
In this dissertation, the trajectory control of the quadcopter is explored and developed with the objective of finding the best way travel in terms of speed and energy consumption. The sensor fusion of several GPS modules is implemented as an algorithm that provides better localization measurements and reduces noise. An attempt to identify the NAZA® attitude controller in order to obtain its mathematical model is also subjects of this thesis. Trajectory algorithms are designed and tested with and without faults in the motors, on the X8 configuration in Simulink®. The main contributions are the improved GPS signal reception and algorithms for an autonomous trajectory following quadcopter. Experiments in the real-world quadcopter were done in order to validate the performance of such contributions. The simulations and experiments presented good performance of the quadcopter’s behavior when integrating the filtered GPS signal. Simulations show the continuous improvement for trajectory generation and following of the drone between the three controllers tested (from worst to best): PID, state space feedback and differential flatness.