Development of a method for synthesizing adaptive control systems for unmanned aerial vehicles

Anastasiia Yurievna Serdiukova; Anton Sergeevich Gubankov; Alexander Valerievich Zuev; Dmitry Alexandrovich Yukhimets; Vladislav Vladislav Gorin

Anastasiia Yurievna Serdiukova Institute of Marine Technology Problems named after Academician M.D. Ageev, Far East-ern Branch of the Russian Academy of Sciences
Anton Sergeevich Gubankov Institute of Automation and Control Processes, Far Eastern Branch of the Russian Academy of Sciences https://orcid.org/0000-0002-0934-6222
Alexander Valerievich Zuev Institute of Automation and Control Processes, Far Eastern Branch of the Russian Academy of Sciences
Dmitry Alexandrovich Yukhimets Institute of Automation and Control Processes, Far Eastern Branch of the Russian Academy of Sciences
Vladislav Vladislav Gorin Admiral G.I. Nevelskoy Maritime State University

Keywords: UAV, mathematical model, adaptive control system, nonlinear controller, variable-structure observer.

Abstract

The paper proposes a method for the synthesis of an adaptive control system (CS) for the spatial motion of a quadrotor unmanned aerial vehicle (UAV), ensuring desired dynamic performance under conditions of parametric uncertainty and external disturbances. The proposed CS is designed to maintain stability and tracking accuracy in the presence of model inaccuracies and unknown environmental effects, including time-varying disturbances. The CS has a cascaded structure with an outer position control loop and an inner attitude control loop, implemented using nonlinear position controllers (NPC) and nonlinear attitude controllers (NAC), respectively. Parametric uncertainties and external disturbances are estimated using variable structure observers (VSOs), whose estimates are incorporated into the control laws to provide real-time compensation of uncertainties. The synthesis of the CS and VSOs is based on a mathematical model of the UAV that accounts for the center-of-mass (CM) offset and key dynamic effects. The combined influence of external disturbances and parametric uncertainties is represented in the dynamic equations as an additive disturbance term. The effectiveness of the proposed approach is demonstrated through numerical simulations in stabilization and trajectory tracking tasks.