Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parameters

The optimal design of an airfoil varies across flight conditions, motivating the search for ways to implement adaptive designs. This study proposes an integrated framework for morphing airfoils using shape-memory alloy (SMA) actuators, targeting improved lift-to-drag (L/D) ratios during quasi-steady flight. Airfoils are parameterized using the PARSEC method and optimized using particle swarm optimization (PSO), with CFD evaluations conducted in COMSOL. A PID-controlled SMA model implements the resulting shapes through voltage-controlled deformation, simulated in Simscape. This setup allows aerodynamic performance to be optimized while respecting actuation and control constraints. Validation against benchmark data confirms solver accuracy, and actuator tracking performance is demonstrated with displacement errors below 0.6%. The framework bridges aerodynamic design and real-time implementation, highlighting SMA's suitability for cruise-phase morphing. While the current study focuses on fixed-wing applications, future work may extend the approach to adaptive UAVs or other domains requiring geometry-responsive actuation.