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Self-Scheduled LPV Control of Asymmetric Variable-Span Morphing UAV.

Jihoon Lee1, Seong-Hun Kim1, Hanna Lee1

  • 1Department of Aerospace Engineering, Seoul National University, Seoul 08826, Republic of Korea.

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Summary

This study introduces a new flight control framework for morphing unmanned aerial vehicles (UAVs) using linear parameter-varying (LPV) methods. The proposed system effectively manages UAV flight dynamics and trajectory tracking during wing morphing maneuvers.

Keywords:
autopilotcontrol augmentation systemflight control systemgain schedulinglinear parameter-varying controlmorphing aircraftnonlinear guidancerobust controltrajectory trackingunmanned aerial vehicle

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Area of Science:

  • Aerospace Engineering
  • Control Systems
  • Robotics

Background:

  • Morphing unmanned aerial vehicles (UAVs) offer enhanced aerodynamic performance but present complex control challenges.
  • Traditional control methods struggle with the dynamic changes inherent in morphing aircraft.
  • Linear Parameter-Varying (LPV) control offers a promising approach for handling such time-varying systems.

Purpose of the Study:

  • To propose a novel flight control framework for morphing UAVs using LPV methods.
  • To develop and validate an LPV-based control system for an asymmetric variable-span morphing UAV.
  • To investigate the span morphing strategy's impact on flight control and maneuverability.

Main Methods:

  • Obtained high-fidelity nonlinear and LPV models of an asymmetric variable-span morphing UAV using the NASA generic transport model.
  • Decomposed wing span variations into symmetric and asymmetric morphing parameters for LPV scheduling and control input.
  • Designed LPV-based control augmentation systems and autopilots for tracking flight commands (normal acceleration, sideslip, roll rate, airspeed, altitude, roll angle).
  • Coupled a nonlinear guidance law with autopilots for 3D trajectory tracking.

Main Results:

  • Successfully designed LPV-based control augmentation systems and autopilots for the morphing UAV.
  • Demonstrated the effectiveness of the span morphing strategy in aiding intended maneuvers.
  • Validated the 3D trajectory tracking capability through numerical simulations.

Conclusions:

  • The proposed LPV framework provides an effective solution for the flight control of morphing UAVs.
  • LPV methods enable robust control of UAVs with dynamically changing configurations.
  • The study highlights the potential of LPV control for advanced aerial vehicle applications.