Air Data Sensor Fault Detection and Diagnosis in the Presence of Atmospheric Turbulence: Theory and Experimental Validation With Real Flight Data

Autor:	Qiping Chu, Coen C. de Visser, Erik-Jan van Kampen, Peng Lu
Rok vydání:	2021
Předmět:	Jet (fluid) Scale (ratio) Flight envelope Control and Systems Engineering Control theory Computer science Turbulence Kinematics Aerodynamics Atmospheric model Electrical and Electronic Engineering Fault detection and isolation ComputingMethodologies_COMPUTERGRAPHICS
Zdroj:	IEEE Transactions on Control Systems Technology. 29:2255-2263
ISSN:	2374-0159 1063-6536
Popis:	Managing air data sensor fault detection and diagnosis (FDD) in the presence of atmospheric turbulence is challenging since the effects of faults and turbulence are coupled. Existing FDD approaches cannot decouple the faults from the turbulence. To address this challenge, this brief first proposes a novel kinematic model that incorporates the effects of the turbulence. This model is valid inside the entire flight envelope, and there is no need to design a linear parameter varying system. Then, the double-model adaptive estimation algorithm is extended to achieve unbiased state estimation even in the presence of unknown disturbances. The proposed approach is validated using generated turbulence data with various scale lengths and intensities. More importantly, the proposed approach is successfully validated using the real flight test data of a business jet when it is experiencing atmospheric turbulence.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b14d8d9a68ebcbb8bcb82a66c463d93b https://doi.org/10.1109/tcst.2020.3025725 Zobrazit plný text záznamu