Robust LQR and LQR-PI control strategies based on adaptive weighting matrix selection for a UAV position and attitude tracking control

Unmanned aerial vehicles (UAVs) are subject to the wind and other environmental disturbances that can destabilize them. The high performance and robustness of the Linear Quadratic Regulator (LQR) controllers ensure the ability to reduce the deviations in state trajectories with minimum control effor...

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Published inAlexandria engineering journal Vol. 61; no. 8; pp. 6275 - 6292
Main Authors Sir Elkhatem, Aisha, Naci Engin, Seref
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.08.2022
Elsevier
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Online AccessGet full text
ISSN1110-0168
DOI10.1016/j.aej.2021.11.057

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Abstract Unmanned aerial vehicles (UAVs) are subject to the wind and other environmental disturbances that can destabilize them. The high performance and robustness of the Linear Quadratic Regulator (LQR) controllers ensure the ability to reduce the deviations in state trajectories with minimum control effort. In this paper, the weighting matrices are adjusted automatically via a novel method implemented through state variables matrix of the quadrotor together with a preference factor. This proposed factor is determined by the designer via penalizing or rewarding a certain state of the quadrotor out of others so that the model insufficiencies against disturbances are compensated. The effectiveness of the proposed method of selecting these matrices is evaluated for the cases of LQR and LQR with a PI controller. They were evaluated with respect to the convergence of state variables to their reference values within a specific time and compliance with their desired performance characteristics. The experimental results revealed that both control strategies could stabilize the quadrotor in the desired position and attitude with better performance and robustness characteristics. The results also showed that the LQR-PI control method is a more reliable and effective approach in achieving higher tracking performances compared to the LQR only.
AbstractList Unmanned aerial vehicles (UAVs) are subject to the wind and other environmental disturbances that can destabilize them. The high performance and robustness of the Linear Quadratic Regulator (LQR) controllers ensure the ability to reduce the deviations in state trajectories with minimum control effort. In this paper, the weighting matrices are adjusted automatically via a novel method implemented through state variables matrix of the quadrotor together with a preference factor. This proposed factor is determined by the designer via penalizing or rewarding a certain state of the quadrotor out of others so that the model insufficiencies against disturbances are compensated. The effectiveness of the proposed method of selecting these matrices is evaluated for the cases of LQR and LQR with a PI controller. They were evaluated with respect to the convergence of state variables to their reference values within a specific time and compliance with their desired performance characteristics. The experimental results revealed that both control strategies could stabilize the quadrotor in the desired position and attitude with better performance and robustness characteristics. The results also showed that the LQR-PI control method is a more reliable and effective approach in achieving higher tracking performances compared to the LQR only.
Author Sir Elkhatem, Aisha
Naci Engin, Seref
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Keywords LQR-PI
UAV
LQR
Mass uncertainty
Actuator fault
Weighting matrices
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Snippet Unmanned aerial vehicles (UAVs) are subject to the wind and other environmental disturbances that can destabilize them. The high performance and robustness of...
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SubjectTerms Actuator fault
LQR
LQR-PI
Mass uncertainty
UAV
Weighting matrices
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Title Robust LQR and LQR-PI control strategies based on adaptive weighting matrix selection for a UAV position and attitude tracking control
URI https://dx.doi.org/10.1016/j.aej.2021.11.057
https://doaj.org/article/9308867b3c0e4203bc1616bf0b1a2178
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