Font Size: 
Nikolay V. Kuznetsov, Boris Andrievsky, Alexander M. Popov, Elena V. Kudryashova, Olga A. Kuznetsova

Last modified: 2023-06-29


This paper focuses on the problem of unmanned aerial vehicle (UAV) control in the presence of significant parametric uncertainty for UAV mass and aerodynamics coefficients caused by variations of the payload, fuel, and flight conditions. In the paper, the feedback linearization method is applied to the nonlinear UAV model. A novel version of this approach is implemented for the UAV point mass model transformations for obtaining its linearized spatial motion model. The uncertain mass is introduced into a linearized system, in contrast to the habitual approach, where the feedback-linearized plant dynamics are described by double integrators. Since different movements of the UAV have different rates, the principle of subordinate control is employed in the paper. To ensure the movement of the UAV along the developed trajectory, the article developed onboard simple adaptive control (SAC) algorithms for local control of the spatial and angular movement of the UAV, the synthesis of which uses a detailed (rather than point) model of the UAV dynamics. The task of synthesizing the control law for this is divided into solving such subtasks as controlling the flight speed and altitude, heading, trajectory inclination, acceleration control, and UAV angular movement. Simulation results are presented to demonstrate the quality of the UAV formation flight control system for various conditions.
The simulation results for the realistic UAV model are performed demonstrating the efficiency of the proposed control method. The future works are aimed at the expansion of the suggested method to the decentralized control of the group of UAVs.

Acknowledgment. The work is supported in part by the St. Petersburg State University grant Pure ID 75207094, by the Leading Scientific Schools of the Russian Federation, project NSh-4196.2022.1.1, and by the Ministry of Science and Higher Education of the Russian Federation (government contract agreement No. 471 075-03-2020-045/2 of 9 June 2020).