Intelligent Morphing Wing Flight Control Simulation

This morphing wing unmanned air vehicle (UAV) numerical simulation from Texas A&M University is using computational fluid dynamics (CFD) for the aerodynamics, adaptive action grid (AAG) for the intelligent learning control, and structured adaptive model inverse (SAMI) adaptive control for the flight controller. The integrated combination of both is called adaptive-reinforcement learning control (A-RLC). This video is a full nonlinear dynamical simulation of a morphing UAV flying under closed-loop automatic control. It is flying a cruise, descent, cruise, climb, and cruise flight profile which is pre-specified. The optimal shape changes are not pre-programmed or scheduled. Instead the UAV learns the optimal shape changes and how to morph into them on its own, while maintaining flight stability and trajectory tracking during the shape changes.Texas A&M researchers determined that the A-RLC architecture is good candidate for controlling both the shape changing of a morphing aircraft and the vehicle itself.