Geometric fault detection and isolation filters are known for having excellent fault isolation, fault reconstruction and sensitivity properties under small modeling uncertainty and noise. However they are assumed to be sensitive to model uncertainty and noise. This paper proposes a method to incorporate model uncertainty into the design. First, a geometric filter is designed on the nominal plant. Next a robust model matching problem is solved to design a filter that robustly matches the performance of the geometric filter over the set of uncertain plants. Several existing methods for robust filter synthesis are described to solve the robust model matching problem. It is then shown that the robust model matching problem has an interesting self-optimality property for multiplicative input uncertainty sets. Finally, an aircraft dynamics example is presented to detect and isolate aileron actuator faults to asses the performance of the geometric filter.
|Original language||English (US)|
|Title of host publication||Proceedings of the 18th IFAC World Congress|
|Number of pages||6|
|Edition||1 PART 1|
|State||Published - 2011|
|Name||IFAC Proceedings Volumes (IFAC-PapersOnline)|
|Number||1 PART 1|
Bibliographical noteFunding Information:
⋆This material is based upon work supported by the National Science Foundation under Grant No. 0931931 entitled “CPS: Embedded Fault Detection for Low-Cost, Safety-Critical Systems”. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. This work is supported by the ADDSAFE (Advanced Fault Diagnosis for Safer Flight Guidance and Control) EU FP7 project, Grant Agreement: 233815, Coordinator: Dr. Andrés Marcos. This work is also supported by the Control Engineering Research Group of HAS at Budapest University of Technology and Economics. The authors are also thankful for Zoltán Szabó, for providing insight on geometric FDI methods.
- Aircraft safety
- Analytical redundancy
- Geometric design methods
- Model matching
- Robust filtering