Flight dynamics is a captivating field that delves into the principles governing how aircraft move through the air. It's about understanding the forces and moments that act on an airplane, how they interact, and how we can control them to achieve desired flight paths and performance. From the initial design stages to advanced control systems, flight dynamics is crucial for ensuring an aircraft is stable, maneuverable, and safe.
Our work in flight dynamics explores cutting-edge approaches to aircraft design and analysis, pushing the boundaries of what's possible in aerospace engineering. We're excited to share two key projects that highlight our innovative methodologies:
This project investigates how modern flight control systems can allow for more flexible aircraft designs. Traditionally, airplanes are built with a high degree of inherent stability, which often leads to larger tails and increased drag. By leveraging advanced control systems, we can relax these static stability constraints, potentially leading to smaller tail areas, reduced drag, and enhanced maneuverability for high-performance aircraft. Our study quantifies the extent to which feedback control can compensate for reduced static stability, enabling optimized designs without compromising performance.
Aircraft System Identification Toolbox
This project dives into the powerful technique of system identification, which uses actual flight data to build and refine mathematical models of an aircraft's dynamics. Instead of relying solely on theoretical models, this approach allows engineers to accurately estimate crucial aerodynamic parameters. The core objective is a robust and generalizable methodology, implemented in MATLAB code, for identifying all stability derivatives of any airplane using flight test data. These coefficients are fundamental for designing flight control systems, flight simulators, and predicting aircraft performance. The project demonstrates a robust methodology, which utilizes the capabilities of a specialized Aircraft System Identification Toolbox (ASIT), developed in-house, to extract these derivatives from dynamic response data. While broadly applicable, "The Golf airplane" serves as a specific verification case to validate the code's capability for identifying stability derivatives.