Adaptive robust trajectory tracking control with states-estimation for DJI-F450 quadrotor under multiple unknown disturbances

Abstract A quadrotor unmanned aerial vehicle (UAV) must achieve desired flight missions despite internal uncertainties and external disturbances. This paper proposes an adaptive trajectory tracking control method that attenuates unknown uncertainties and disturbances. Although the quadrotor is underactuated, a fully actuated controller is designed using backstepping control. To avoid repeated derivatives of control inputs, a dynamic surface method introduces a filter and auxiliary controller. Lyapunov criteria guide adaptive laws for tuning controller gain and filters. A low-power observer is integrated for state estimation. Additionally, a disturbance observer is developed and combined with the control scheme to handle unknown disturbances. Simulations on a DJI F450 quadrotor demonstrate that the proposed control algorithm offers strong trajectory-tracking performance and system stability under multiple uncertainties and external disturbances during flight.

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Publication Details

Journal
Journal of Navigation
Published
2025-01-01
DOI
https://doi.org/10.1017/s0373463325000189
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Adaptive robust trajectory tracking control with states-estimation for DJI-F450 quadrotor under multiple unknown disturbances

Meng Joo Er, Nigar Ahmed
Journal of Navigation
Adaptive Control of Nonlinear Systems
article

Adaptive robust trajectory tracking control with states-estimation for DJI-F450 quadrotor under multiple unknown disturbances

Meng Joo Er, Nigar Ahmed
article en

Abstract

Abstract A quadrotor unmanned aerial vehicle (UAV) must achieve desired flight missions despite internal uncertainties and external disturbances. This paper proposes an adaptive trajectory tracking control method that attenuates unknown uncertainties and disturbances. Although the quadrotor is underactuated, a fully actuated controller is designed using backstepping control. To avoid repeated derivatives of control inputs, a dynamic surface method introduces a filter and auxiliary controller. Lyapunov criteria guide adaptive laws for tuning controller gain and filters. A low-power observer is integrated for state estimation. Additionally, a disturbance observer is developed and combined with the control scheme to handle unknown disturbances. Simulations on a DJI F450 quadrotor demonstrate that the proposed control algorithm offers strong trajectory-tracking performance and system stability under multiple uncertainties and external disturbances during flight.

Journal of NavigationVol. 78(1)
Centre for Artificial Intelligence and Robotics (IN), Dalian Maritime University (CN)
Openalex Percentile: Top 82%
Adaptive Control of Nonlinear Systems
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