Real-Time Performance Optimization for a Camber Morphing Wing Based on Domain Incremental Model under Concept Drifting

Abstract

Compared with traditional wings equipped with conventional control surfaces, variable-camber morphing wings have become a hot research topic in the field of aviation due to their ability to maintain a smooth and continuous overall shape while ensuring excellent aerodynamic performance. This study focuses on a high aspect ratio wing with a continuous variable-camber trailing edge. Two precision models were constructed: an aerodynamic model and an aeroelastic model. Based on simulation data obtained from these models, we developed and updated a surrogate model for the wing, with particular emphasis on an incremental modeling approach that takes concept drift into account. Subsequently, using the aforementioned models, we conducted real-time optimization with feedback considerations to reduce drag, lower stress on the main beam, and minimize actuator energy under either steady or slowly varying target lift conditions. Notably, the optimization process resulted in a 4% reduction in drag or a significant decrease of 18.3% in maximum stress. Through computational comparisons, the accuracy of the proposed surrogate model and incremental learning method is demonstrated, along with their efficiency in the context of optimization problems.

Keywords

• shape optimization
• incremental learning
• concept drift
• camber morphing wing
• real time