*Result*: Adaptive Tracking Differentiator with Feature Recognition for Signal Processing in High‐Altitude Test Facilities.

*The ambient pressure is an important indicator for ensuring stable and efficient testing of the aeroengine in the high‐altitude test (HAT) facilities. With the complex and quickly changing test environment and storage limitation of the underlying hardware, processing the pressure signals to access its filtering and differentiating signals to participate in designing feedback controller becomes difficult. The integration step of a differentiator algorithm, which is typically closely related to the sampling period, affects the performances of filtering and differentiating. In this work, a feature recognition based adaptive algorithm is proposed to enable the tracking differentiator (TD) by adaptively selecting an appropriate integration step in real‐time. In particular, the sampled signals are transformed into images and analyzed by a proposed feature recognition algorithm. This algorithm can transform the real‐time signals into an indice of system's dynamic characteristic. Simulation and experiment results show that the proposed adaptive TD algorithm can effectively improve the filtering and differentiating performances compared with the original TD, and meet the signal processing requirements of HAT facilities. [ABSTRACT FROM AUTHOR]

Copyright of IET Control Theory & Applications (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)*