Lejun Chen
Application of model-based LPV actuator fault estimation for an industrial benchmark
Chen, Lejun; Patton, Ron; Goupil, Philippe
Authors
Professor Ron Patton R.J.Patton@hull.ac.uk
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 |
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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. |
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Copyright Statement
©2017 The University of Hull
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