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

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.