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Extended observer based on adaptive second order sliding mode control for a fixed wing UAV.

Herman Castañeda1, Oscar S Salas-Peña2, Jesús de León-Morales2

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Summary

This study introduces an adaptive sliding mode control for fixed-wing unmanned aerial vehicles, enhancing performance and disturbance rejection without needing to know disturbance bounds. The novel approach ensures robust flight control and stability.

Keywords:
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Area of Science:

  • Aerospace Engineering
  • Control Systems
  • Robotics

Background:

  • Fixed-wing unmanned aerial vehicles (UAVs) require robust control systems for stable flight.
  • External disturbances and unmeasurable states pose significant challenges to UAV control.
  • Existing control methods may require knowledge of disturbance bounds or lead to overestimation of control gains.

Purpose of the Study:

  • To design an adaptive second-order sliding mode control (SMC) for attitude and airspeed control of fixed-wing UAVs.
  • To develop an extended observer for estimating unmeasurable states and external disturbances.
  • To ensure closed-loop stability and robustness against unknown disturbances.

Main Methods:

  • Adaptive second-order sliding mode control (SMC) design.
  • Extended observer for state and disturbance estimation.
  • Stability analysis using sufficient conditions for observer-based control.
  • 6-DOF simulation model for performance evaluation.

Main Results:

  • The proposed adaptive SMC controller improves performance under varying operating conditions.
  • The control strategy is robust to external disturbances without requiring prior knowledge of their bounds.
  • The extended observer effectively estimates unmeasurable states and disturbances.
  • Simulation results demonstrate superior performance compared to active disturbance rejection control (ADRC) based SMC.

Conclusions:

  • The developed adaptive second-order SMC with an extended observer provides a robust and effective solution for fixed-wing UAV attitude and airspeed control.
  • The method enhances flight performance and stability in the presence of uncertainties and disturbances.
  • The approach offers advantages by not requiring disturbance bound estimations, thus avoiding control gain overestimation.