Data-driven control could make aircraft systems smarter and more reliable
Measured flight data can help improve aircraft controller design, supporting more adaptive trajectory tracking and reliable autonomous systems.
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A new study presents an improved data-driven strategy for aircraft controller design, offering a model-free approach to flight control based on measured input-output data.
Published in Scientific Reports, the research proposes a framework that integrates data-driven identification, control and validation. Instead of depending entirely on predefined mathematical models, the method uses measured aircraft data to build an auxiliary model, design a parameterised controller and verify its performance.
The study addresses a key challenge in aviation engineering: aircraft systems operate under complex, nonlinear and time-varying conditions. In this context, traditional controller design can be limited when the full system model is difficult to obtain or validate.
The proposed strategy was tested in an aircraft flight system application focused on trajectory tracking. The results showed stable performance, with the aircraft following a predetermined path and producing a more stable error curve than classical PID control.
Beyond aviation, the research contributes to the development of adaptive control methods for autonomous systems, robotics, intelligent mobility and other engineering applications where reliable control is essential.
For UNICARIBE, this publication strengthens its research agenda in advanced engineering, automation, data-driven systems and intelligent control.
Read the full article: https://www.nature.com/articles/s41598-025-23233-2