This paper compares three model-based methods for detecting and isolating stuck control surface faults on a small unmanned aircraft. The first method is parity-space based and compares a sensor measurement against a model-based prediction of the same quantity. The second method is observer-based and involves robust estimation for linear parameter-varying systems. The third method is also observer-based and involves multiple model adaptive estimation. The performance of the three methods are compared using flight data. The comparison shows that the three methods have different detection performance and runtime. The selection of a particular method depends on the application requirements and implementation constraints.
Bibliographical noteFunding Information:
The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 690811 and the Japan New Energy and Industrial Technology Development Organization under grant agreement No. 062600 as a part of the EU/Japan joint research project entitled ‘Validation of Integrated Safety-enhanced Intelligent flight cONtrol (VISION)’. This research was also funded by the National Science Foundation, USA under Grant No. NSF/CNS-1329390 entitled “CPS: Breakthrough: Collaborative Research: Managing Uncertainty in the Design of Safety-Critical Aviation Systems”. The first author acknowledges financial support from the University of Minnesota, USA through the 2017–2018 Doctoral Dissertation Fellowship. The authors thank the following individuals: T. Colten of Sentera for donating the Vireo aircraft; C. Olson for the flight software, controller implementation, autoland trajectory, head-up display, and piloting; N. Carter, R. Condron, L. Heide, A. Mahon, C. Regan, and B. Taylor for aircraft integration and testing.
- Fault detection and isolation
- Linear parameter-varying systems
- Multiple model adaptive estimation
- Robust estimation
- Small unmanned aircraft systems