Nonlinear Control of Quadrotor: Feedback Linearization and Sliding Mode Control

Quadrotor Unmanned Aerial Vehicles (UAVs) are inherently underactuated, as they are expected to track six outputs using only four rotors. Due to their nonlinear dynamics, nonlinear control techniques have gained popularity for controlling quadrotors. This study, therefore, compares two prominent nonlinear control methods: adaptive Feedback Linearization (FBL) and robust Sliding Mode Control (SMC). Lyapunov stability analysis was conducted to validate the control design, followed by MATLAB/SIMULINK simulations. The results show that adaptive FBL demonstrated superior performance in position and attitude tracking compared to its robust SMC counterpart based on the root mean square error metric.

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Publication Details

Published
2024-12-28
DOI
https://doi.org/10.1109/mepe64515.2024.11115693
Citations
1
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.33
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article

Nonlinear Control of Quadrotor: Feedback Linearization and Sliding Mode Control

Farouq Aliyu, Taiba Kouser, Abdulrahman Aliyu, Luai Muhammad Alhems
1 citations
Adaptive Control of Nonlinear Systems
0.33
article

Nonlinear Control of Quadrotor: Feedback Linearization and Sliding Mode Control

Farouq Aliyu, Taiba Kouser, Abdulrahman Aliyu, Luai Muhammad Alhems
article en
1 citations

Abstract

Quadrotor Unmanned Aerial Vehicles (UAVs) are inherently underactuated, as they are expected to track six outputs using only four rotors. Due to their nonlinear dynamics, nonlinear control techniques have gained popularity for controlling quadrotors. This study, therefore, compares two prominent nonlinear control methods: adaptive Feedback Linearization (FBL) and robust Sliding Mode Control (SMC). Lyapunov stability analysis was conducted to validate the control design, followed by MATLAB/SIMULINK simulations. The results show that adaptive FBL demonstrated superior performance in position and attitude tracking compared to its robust SMC counterpart based on the root mean square error metric.

King Fahd University of Petroleum and Minerals (SA)
Affordable and clean energy
Openalex Percentile: Top 35%
Adaptive Control of Nonlinear Systems
0.33
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