Implementation and test of retrospective cost adaptive controller for a quadcopter with varying configuration parameters

The demand for better efficiency, challenging dynamics, flawless systems and autotuning features has directed the attention of researchers to adaptive controllers. These controllers have been widely developed and implemented for a vast range of applications. If they are well designed, they can improve the performance and simultaneously expand the operational range, in contrast to the trade-off that is commonly observed in robust controllers. Another important feature of these controllers is their capability to compensate for unmodelled dynamics. Furthermore, conventional controllers lack the ability to properly handle changes in the model that could be caused by a failure or environmental variations. The control of unmanned aerial vehicles (UAVs) is one of the many applications in which these controllers are implied and tested. The use of multirotors for civil and military applications is continuously increasing but their unstable dynamics in the absence of a proper controller, in addition to the higher complexity and more challenging dynamics, promote the need for better and flexible control techniques, such as adaptive controllers. The progressive need for the improvement of the quadcopter's performance, minimisation of modelling data and the possibility to integrate fail-safe and autotuning features were the motivation for this research. Although independent command-following and disturbance rejection of constant and harmonic signals were successfully achieved, multiple limitations regarding the adaptability of the controller are found. This thesis provides a description of the design and implementation of a position controller for a quadcopter using a retrospective cost adaptive controller (RCAC). First, the RCAC is briefly introduced and a description of its working principle and main components needed for its computation is given. Secondly, the implementation and validation of the algorithms are analysed and the results are linked with the equations to provide insight into the expected behaviour of the controller. Then, the dynamic model and the structure of the attitude control are described. Finally, the integration of the RCAC for position control is explained and based on the obtained results, an evaluation of the performance and the influence of the parameters is provided.Master of Science (Aerospace Engineering