Presntations
1. Closed-Loop Stability Margin Identification From Flight-Test Data Using DFT, Spectral Methods and Nonlinear Frequency
by H. Alpay Küçüker, Turkish Aerospace Industries
Flight-control-law clearance relies on an accurate understanding of loop-transfer characteristics and the associated stability margins, especially gain and phase margins. These quantities are often obtained from numerically linearized models; however, their reliability\ should be confirmed using higher-fidelity simulations and actual flight-test data. This paper presents a practical method for reconstructing aircraft loop-transfer characteristics directly from a closed-loop control system, without requiring loop breakage or dedicated open-loop testing. The approach uses measurable internal control signals to estimate loop gain under normal operating conditions. Three complementary identification techniques are examined: Discrete Fourier Transform (DFT), spectral density estimation with coherence analysis, and nonlinear frequency response (NLFR) identification. The DFT and spectral approaches are applied to flight-test data from a new jet trainer aircraft across multiple Mach number and altitude conditions. The NLFR method is implemented in a high-fidelity engineering simulator to assess nonlinear effects and provide an independent validation reference. The identified frequency responses are compared with numerically linearized loop-transfer models in terms of magnitude, phase, gain margin, and phase margin. Results show that the proposed framework successfully captures the dominant loop dynamics within the excited frequency range and provides\ meaningful stability-margin estimates from closed-loop flight data. Strong agreement\ is obtained for most longitudinal-axis conditions, while selected directional-axis cases show deviations that suggest limitations of conventional linearization in the presence of coupled nonlinear dynamics. The study also highlights the importance of excitation quality, coherence\ level, and signal-processing choices in practical flight-test identification. Overall, the proposed methodology offers an operationally relevant tool for model validation, control-law clearance, and future real-time flight-envelope expansion activities
2. Flight Test Techniques for Assessing Cross-Coupling between Longitudinal and Lateral-Directional Dynamics
by Maj. André Alves, Brazilian Air Force
This paper investigates the coupling effects between longitudinal and lateral–directional dynamics of an EMB-312 Tucano aircraft using flight test data, with the objective of improving the fidelity of a Level-6 Flight Training Device (FTD). A dedicated flight test campaign was
conducted to excite the aircraft dynamics over a range of airspeeds and under partially uncorrelated lift and thrust conditions, enabling the identification of nonlinear aerodynamic interactions not captured by conventional decoupled models. Stability and control derivatives were estimated using system identification techniques and subsequently modeled as functions\ of physically meaningful variables, including angle of attack, thrust coefficient, and propeller advance ratio. A structured interpolation-based model stitching procedure was then applied to\ extend the locally identified models across the flight envelope. The results show that several derivatives traditionally associated with a single motion axis are significantly influenced by variables from other axes, confirming the presence of non-negligible cross-coupling effects. Model validation using independent flight test data demonstrated satisfactory predictive capability, with Theil’s Inequality Coefficient (TIC) values within acceptable limits for most variables. These findings indicate that cross-coupling effects play a significant role in aircraft
dynamics and should be accounted for in high-fidelity simulation models. Furthermore, the results demonstrate that such effects can be effectively captured through properly designed flight test campaigns combined with data-driven modeling and physically based interpolation
strategies.
3. A Framework for Extracting Stable Cruise Segments from Operationally Observed Performance Data
by Lance Bays, George Washington University.
Modern commercial airliners record an ever-expanding range of parameters that describe aircraft state and system behavior. An important application of these data is aircraft performance monitoring, which identifies aircraft within a fleet that exhibit excessive fuel
consumption. Recently, researchers have applied new technologies and advanced computational models that offer potential improvements over legacy performance monitoring systems. However, analyses using data from entire flights must contend with transient conditions,
unsteady forces, and aircraft configuration changes during non-cruise phases, such as takeoff, climb, turning, approach, and landing. Many of these segments are difficult to model and contribute little to the identification of trends in aircraft fuel consumption.
In commercial airline operations, the phase of flight that consumes the most fuel is cruise, during which aerodynamic and propulsive forces are in near equilibrium, and deviations from expected performance are more readily detected. This paper presents a computational
framework that automatically extracts analysis-ready steady-state cruise data from raw operational datasets. A sliding window approach identifies intervals that meet defined cruise criteria, then analyzes aerodynamic, propulsive, and fuel-efficiency metrics for those intervals.
This work addresses a key research gap: the lack of generalized, scalable methods for extracting large volumes of high-quality, analysis-ready cruise data from operational datasets, and introduces a practical framework to do so. A sample implementation using an operational
dataset from NASA reveals several novel observations in the measured and derived parameters. The processed data, provided in an open-access repository, are available to the community for
developing advanced performance-monitoring methods.