Adaptive Wing Drag Control Using Online Aeroelastic Model Identification
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Solution Overview
Problem
Conventional drag optimization technologies for aircraft are limited by relying on a single design point and are not adaptive to varying aircraft configurations and flight conditions, leading to suboptimal aerodynamic efficiency and increased fuel consumption.
Innovation Solution
A real-time drag optimization control framework that uses a computer-implemented method to perturb flap sections with excitation signals, detect changes in aerodynamic parameters, and perform online model identification to dynamically optimize drag and lift, allowing for continuous adaptation to changing flight conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If table lookup method with fixed aircraft model is used, then drag optimization is simple to implement, but adaptability to varying aircraft configurations and flight conditions deteriorates
Solution Approach 1:
The patent implements dynamic model identification that continuously adapts to changing flight conditions, aircraft configurations, and aeroelastic deformations. The system transitions from static table lookup to real-time dynamic modeling, allowing the drag optimization to respond adaptively to varying flight envelopes, weight changes, and wing deformations while maintaining computational feasibility through efficient identification algorithms.
2Productivity
If adaptive wing technologies are implemented, then aerodynamic efficiency is improved, but system complexity increases
Solution Approach 1:
The patent employs feedback mechanisms where sensors continuously monitor actual flight conditions, wing deformations, and aerodynamic parameters. This real-time feedback is fed into the model identification system, which updates the aircraft model and adjusts flap configurations accordingly. The closed-loop feedback control enables adaptive wing technologies to maintain optimal aerodynamic efficiency while managing system complexity through intelligent control algorithms.
Solution Approach 2:
The system performs self-identification of aircraft models without requiring external intervention or extensive pre-programming. The model identification algorithm automatically adapts to the specific aircraft configuration and flight conditions by processing sensor data in real-time, enabling the adaptive wing system to self-optimize aerodynamic performance across varying operating conditions without increasing operational complexity.
3Adaptability or versatility
If online model identification is performed in real-time, then adaptability to changing conditions is improved, but computational load increases
Solution Approach 1:
The patent implements a balanced approach where model identification is performed at appropriate intervals and with appropriate detail based on the rate of change of flight conditions. The system identifies models online in real-time but manages computational load by focusing on critical parameters and using efficient identification algorithms that provide sufficient accuracy without excessive computational burden, achieving real-time adaptation with acceptable power consumption.
Data Source
AI summary
Processes for real-time drag optimization control for aeroelastic wing structures are disclosed. Adaptive reconfiguration of aircraft control surfaces by an online real-time drag optimization control approach to reduce or minimize drag may reduce the amount of fuel that is consumed by the aircraft during flight. The input data may be obtained from sensor information pertaining to the wing deflection and aircraft state information. The optimization approach may compute an optimal solution of the distributed flight control surface deflections that are integrated in a flight path angle flight control system.