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Application of model-based LPV actuator fault estimation for an industrial benchmark

Chen, Lejun; Patton, Ron; Goupil, Philippe

Authors

Lejun Chen

Profile image of Ron Patton

Professor Ron Patton R.J.Patton@hull.ac.uk
Emeritus Professor of Control and Intelligent Systems Engineering

Philippe Goupil



Abstract

To bridge the gap between model-based fault diagnosis theory and the industry practice, a linear parameter varying H_/H∞ fault estimation approach is applied to a high fidelity nonlinear aircraft benchmark, to deal with the various actuator fault detection scenarios which can result in the abnormal aircraft configuration. To facilitate the industry calculating the computational load of the fault estimation approach, the design is fully coded using the flight control computer software library. Furthermore, the robustness performance of the fault estimation approach is evaluated using the parametric simulation and the Monte Carlo campaign supported by a functioning engineering simulator despite the aerodynamic database uncertainties and measurements errors over a wide range of the flight envelope.

Citation

Chen, L., Patton, R., & Goupil, P. (2016). Application of model-based LPV actuator fault estimation for an industrial benchmark. Control engineering practice, 56, 60-74. https://doi.org/10.1016/j.conengprac.2016.08.003

Acceptance Date Aug 2, 2016
Online Publication Date Aug 21, 2016
Publication Date 2016-11
Deposit Date Feb 12, 2016
Publicly Available Date Aug 21, 2016
Journal Control engineering practice
Print ISSN 0967-0661
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 56
Pages 60-74
DOI https://doi.org/10.1016/j.conengprac.2016.08.003
Keywords Fault estimation; Mixed H_/H∞ optimisation; Fault detection and diagnosis
Public URL https://hull-repository.worktribe.com/output/385391
Publisher URL http://www.sciencedirect.com/science/article/pii/S0967066116301666
Additional Information Authors' accepted manuscript of article published in: Control engineering practice, 2016, v.56.
Contract Date Feb 12, 2016

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