intelligent control of a tailsitter uav during transition flight: a feedback linearization approach

This study introduces a hybrid algorithm designed for trajectory tracking control during thetransition flight of a tailsitter unmanned aerial vehicle (uav), employing an integration ofneural networks and a genetic optimization algorithm. the tailsitter uav ducted fan tailsitter,which has been augmented with two additional wings to enhance its flight capabilities. thefoundation of the intelligent controller lies in the feedback linearization method, withperformance enhancements achieved through online neural network training coupled with agenetic optimization algorithm. to validate the effectiveness of the proposed algorithm incontrolling the uav during transition flight, simulations were conducted within the matlab-simulink software environment.