Robust Adaptive Formation Control of Fixed Wing UAVs Using Disturbance Estimators

This paper presents the formation control of multiple homogeneous fixed-wing unmanned aerial vehicles subjected to parameter perturbations and external disturbances. A leader-follower with virtual leader formation architecture is used, and the communication between the vehicles is modelled using a directed graph. A distributed model reference adaptive control strategy is used for the formation acquisition and maintenance. The robustification of the control is achieved using a disturbance estimator developed to estimate and cancel out the effect of the disturbances on the dynamic model. In this formulation, the designed control law does not require any information about the magnitude of the disturbance, or derivative of the states. The simulation results validate the effectiveness of the proposed control strategy.

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Publication Details

Published
2024-11-19
DOI
https://doi.org/10.1109/cinti63048.2024.10830840
Citations
1
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.35
Controls
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Robust Adaptive Formation Control of Fixed Wing UAVs Using Disturbance Estimators

Stephen Kimathi, Béla Lantos
1 citations
Distributed Control Multi-Agent Systems
0.35
article

Robust Adaptive Formation Control of Fixed Wing UAVs Using Disturbance Estimators

Stephen Kimathi, Béla Lantos
article en
1 citations

Abstract

This paper presents the formation control of multiple homogeneous fixed-wing unmanned aerial vehicles subjected to parameter perturbations and external disturbances. A leader-follower with virtual leader formation architecture is used, and the communication between the vehicles is modelled using a directed graph. A distributed model reference adaptive control strategy is used for the formation acquisition and maintenance. The robustification of the control is achieved using a disturbance estimator developed to estimate and cancel out the effect of the disturbances on the dynamic model. In this formulation, the designed control law does not require any information about the magnitude of the disturbance, or derivative of the states. The simulation results validate the effectiveness of the proposed control strategy.

Budapest University of Technology and Economics (HU)
Affordable and clean energy
Openalex Percentile: Top 34%
Distributed Control Multi-Agent Systems
0.35
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