Robust Nonlinear Control with Estimation of Disturbances and Parameter Uncertainties for UAVs and Integrated Brushless DC Motors

Unmanned Aerial Vehicles (UAVs) have become increasingly prevalent in various applications, ranging from surveillance to package delivery. Achieving precise control of UAV position while enhancing robustness against uncertainties and disturbances remains a critical challenge. In this study, we propose a robust nonlinear control system for a UAV and its actuators, focusing on accurately controlling the position reference vector and improving robustness against parameter uncertainties and external disturbances. The control strategy employs two control loops: an outer loop for the UAV frame and an inner loop for the UAV actuators. The outer loop generates the required angular velocities for the actuators to follow the reference position vector using the UAV’s output and the inner loop ensures that the actuators track these angular velocity references. Both control loops utilize PI-like controllers for simplicity. The proposed system incorporates nonlinear control techniques and estimation strategies for disturbances and parameter variations, enabling dynamic adaptation to changing environmental conditions. Numerical simulations were performed using both Simulink® and the simulated PX4 Autopilot environment, showing the effectiveness of the proposed control system in achieving precise position control and robust performance for both the UAV and its actuators in the presence of uncertainties and disturbances. These results underscore the potential applicability of the control system in other UAV operational scenarios.

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Publication Details

Journal
Drones
Published
2024-08-30
DOI
https://doi.org/10.3390/drones8090447
Citations
2
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.66

Funders

Controls
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article

Robust Nonlinear Control with Estimation of Disturbances and Parameter Uncertainties for UAVs and Integrated Brushless DC Motors

Claudia Verónica Vera Vaca, Claudia Carolina Vaca García, S. Di Gennaro, Cuauhtémoc Acosta Lúa
2 citations
Drones
Adaptive Control of Nonlinear Systems
0.66
article

Robust Nonlinear Control with Estimation of Disturbances and Parameter Uncertainties for UAVs and Integrated Brushless DC Motors

Claudia Verónica Vera Vaca, Claudia Carolina Vaca García, S. Di Gennaro, Cuauhtémoc Acosta Lúa
article en
2 citations

Abstract

Unmanned Aerial Vehicles (UAVs) have become increasingly prevalent in various applications, ranging from surveillance to package delivery. Achieving precise control of UAV position while enhancing robustness against uncertainties and disturbances remains a critical challenge. In this study, we propose a robust nonlinear control system for a UAV and its actuators, focusing on accurately controlling the position reference vector and improving robustness against parameter uncertainties and external disturbances. The control strategy employs two control loops: an outer loop for the UAV frame and an inner loop for the UAV actuators. The outer loop generates the required angular velocities for the actuators to follow the reference position vector using the UAV’s output and the inner loop ensures that the actuators track these angular velocity references. Both control loops utilize PI-like controllers for simplicity. The proposed system incorporates nonlinear control techniques and estimation strategies for disturbances and parameter variations, enabling dynamic adaptation to changing environmental conditions. Numerical simulations were performed using both Simulink® and the simulated PX4 Autopilot environment, showing the effectiveness of the proposed control system in achieving precise position control and robust performance for both the UAV and its actuators in the presence of uncertainties and disturbances. These results underscore the potential applicability of the control system in other UAV operational scenarios.

DronesVol. 8(9)
Universidad de Guadalajara (MX), University of L'Aquila (IT), Tecnológico Nacional de México (MX), Universidad de la Ciénega (MX)
Consejo Nacional de Ciencia y Tecnología
Openalex Percentile: Top 31%
Adaptive Control of Nonlinear Systems
0.66
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