Feedback linearization approach for adaptive control of UAV spatial motion

Boris Andrievsky; Alexander M. Popov; Nikolay V. Kuznetsov; Elena V. Kudryashova; Olga A. Kuznetsova

Boris Andrievsky Faculty of Mathematics and Mechanics, \\ Saint Petersburg University, Saint Petersburg 198504, Russia
Alexander M. Popov Baltic State Technical University "VOENMEH" named after D.F. Ustinov, \\Saint Petersburg 190005, Russia
Nikolay V. Kuznetsov Institute for Problems in Mechanical Engineering of the Russian Academy of Sciences, \\Saint Petersburg 199178, Russia
Elena V. Kudryashova Faculty of Mathematics and Mechanics, \\ Saint Petersburg University, Saint Petersburg 198504, Russia} \par\noindent$^2${Institute for Problems in Mechanical Engineering of the Russian Academy of Sciences, \\Saint Petersburg 199178, Russia
Olga A. Kuznetsova Faculty of Mathematics and Mechanics, \\ Saint Petersburg University, Saint Petersburg 198504, Russia

Abstract

This paper addresses the control challenges encountered by unmanned aerial vehicles (UAVs) in the presence of significant parametric uncertainties related to the UAV's mass and aerodynamic coefficients. These uncertainties stem from variations in payload, fuel, and flight conditions. To tackle this issue, the paper applies the feedback linearization method to the nonlinear UAV model. Given that different UAV maneuvers involve varying rates of change, the paper adopts a hierarchical control approach. The primary objective is to ensure the UAV smoothly tracks a predefined trajectory. To achieve this, the paper develops onboard adaptive control algorithms designed to manage both translational and rotational movements of the UAV. These algorithms utilize a comprehensive dynamic model of the UAV in their synthesis, rather than relying on a simplified point model. To effectively address the synthesis of control laws, the paper decomposes it into subproblems, encompassing velocity and altitude control, heading control, trajectory inclination, acceleration control, and angular motion control. Simulation results employing a realistic UAV model are presented to illustrate the effectiveness of the proposed control methodology.