Implementation of real-time moving horizon estimation for robust air data sensor fault diagnosis in the RECONFIGURE benchmark

Yiming Wan, Tamas Keviczky

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

This paper presents robust fault diagnosis and estimation for the calibrated airspeed and angle-of-attack sensor faults in the RECONFIGURE benchmark. We adopt a low-order longitudinal model augmented with wind dynamics. In order to enhance sensitivity to faults in the presence of winds, we propose a constrained residual generator by formulating a constrained moving horizon estimation problem and exploiting the bounds of winds. The moving horizon estimation problem requires solving a nonlinear program in real time, which is challenging for flight control computers. This challenge is addressed by adopting an efficient structure-exploiting algorithm within a real-time iteration scheme. Specific approximations and simplifications are performed to enable the implementation of the algorithm using the Airbus graphical symbol library for industrial validation and verification. The simulation tests on the RECONFIGURE benchmark over different flight points and maneuvers show the efficacy of the proposed approach.
Original languageEnglish
Title of host publicationIFAC-PapersOnLine
Subtitle of host publicationProceedings 20th IFAC Symposium on Automatic Control in Aerospace (ACA 2016)
EditorsJ. de Lafontaine
Place of PublicationLaxenburg, Austria
PublisherElsevier
Pages64-69
Volume49-17
DOIs
Publication statusPublished - 2016
Event20th IFAC Symposium on Automatic Control in AerospaceACA 2016 - Sherbrooke, Quebec, Canada
Duration: 21 Aug 201625 Aug 2016

Publication series

NameIFAC-PapersOnLine
Number17
Volume49

Conference

Conference20th IFAC Symposium on Automatic Control in AerospaceACA 2016
CountryCanada
CitySherbrooke, Quebec
Period21/08/1625/08/16

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