<p>This paper tackles the challenge of achieving robust control for the wing rock motion observed in slender delta wings. The behavior of wing rock, which changes with different angles of attack, is highly unpredictable and influenced by external disturbances. On the other hand, factors such as unmodeled dynamics may severely affect the system's performance. The system state measurements may also be unavailable due to the lack of sufficient instrumentations. To deal with these problems, an extended state observer-based robust controller in the present study is designed to estimate the system's states along with the system’s uncertainty. The standout aspect of the suggested design is that it does not rely on an exact model of the system or detailed information about uncertainties. In addition, the proposed approach is model-free and does not require roll rate feedback for control implementation. Lyapunov analysis is used to verify stability, ensuring that all errors remain bounded within specific limits. Simulation results confirm that the suggested control strategy effectively regulates the rolling motion despite uncertainties, including external disturbances and unmodeled dynamics. Finally, the outcomes of the proposed method are contrasted with two cutting-edge approximation techniques to showcase the precision and efficiency of the suggested controller design.</p>

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Suppressing wing rock motion through differential equation solutions as an extended state observer

  • Saleh Mobayen,
  • Alireza Izadbakhsh

摘要

This paper tackles the challenge of achieving robust control for the wing rock motion observed in slender delta wings. The behavior of wing rock, which changes with different angles of attack, is highly unpredictable and influenced by external disturbances. On the other hand, factors such as unmodeled dynamics may severely affect the system's performance. The system state measurements may also be unavailable due to the lack of sufficient instrumentations. To deal with these problems, an extended state observer-based robust controller in the present study is designed to estimate the system's states along with the system’s uncertainty. The standout aspect of the suggested design is that it does not rely on an exact model of the system or detailed information about uncertainties. In addition, the proposed approach is model-free and does not require roll rate feedback for control implementation. Lyapunov analysis is used to verify stability, ensuring that all errors remain bounded within specific limits. Simulation results confirm that the suggested control strategy effectively regulates the rolling motion despite uncertainties, including external disturbances and unmodeled dynamics. Finally, the outcomes of the proposed method are contrasted with two cutting-edge approximation techniques to showcase the precision and efficiency of the suggested controller design.