Robust Model Reference Fault Detection and Identification System for Fixed Wing Aircrafts Article Swipe
R. Jaganraj
,
Rajkumar Velu
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.4273/ijvss.10.5.14
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.4273/ijvss.10.5.14
Fault Detection and Identification system (FDI) and Fault Tolerant Flight Control (FTFC) system are used to correct the faulty operation of an aircraft. Both FDIs and FTFCs have operational disadvantages due to their inherent limitation of fault source identification. This paper presents the design and implementation of a robust model reference fault detection and identification (MRFDI) system on a fixed-wing aircraft for identifying actuator fault, instrument fault and presence of any uncertainties. The proposed MRDFI fuses the real-time parameters and actuator feedback to combine the advantages of data driven and model reference FDI that makes robust fault estimation. The MRFDI system is implemented on a typical aircraft altitude hold autopilot simulation environment with a predefined fault scenario. The fault scenario includes a faulty elevator, a faulty skin-implantable sensor and wind gust as environmental uncertainty. The MRFDI performs logical analysis to detect fault using state-dependent real-time parameters and state-independent skin implantable sensor. This two-step fault detection method makes MRFDI robust to any type of fault identification. The results show that the MRFDI detects and distinguishes faults in actuator, instrument and any of the listed uncertainties thrown by the environment accurately.
Related Topics
Concepts
Fault detection and isolation
Autopilot
Fault (geology)
Actuator
Identification (biology)
Stuck-at fault
Fault indicator
Engineering
Control theory (sociology)
Control engineering
Robustness (evolution)
Computer science
Real-time computing
Control (management)
Artificial intelligence
Botany
Biochemistry
Gene
Biology
Geology
Chemistry
Seismology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.4273/ijvss.10.5.14
- OA Status
- hybrid
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2908374679
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2908374679Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.4273/ijvss.10.5.14Digital Object Identifier
- Title
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Robust Model Reference Fault Detection and Identification System for Fixed Wing AircraftsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
- Publication date
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2018-12-28Full publication date if available
- Authors
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R. Jaganraj, Rajkumar VeluList of authors in order
- Landing page
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https://doi.org/10.4273/ijvss.10.5.14Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://doi.org/10.4273/ijvss.10.5.14Direct OA link when available
- Concepts
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Fault detection and isolation, Autopilot, Fault (geology), Actuator, Identification (biology), Stuck-at fault, Fault indicator, Engineering, Control theory (sociology), Control engineering, Robustness (evolution), Computer science, Real-time computing, Control (management), Artificial intelligence, Botany, Biochemistry, Gene, Biology, Geology, Chemistry, SeismologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.sensor | 127 |
| abstract_inverted_index.source | 37 |
| abstract_inverted_index.system | 4, 12, 56, 100 |
| abstract_inverted_index.thrown | 184 |
| abstract_inverted_index.(MRFDI) | 55 |
| abstract_inverted_index.Control | 10 |
| abstract_inverted_index.combine | 83 |
| abstract_inverted_index.correct | 16 |
| abstract_inverted_index.detects | 171 |
| abstract_inverted_index.logical | 137 |
| abstract_inverted_index.results | 166 |
| abstract_inverted_index.sensor. | 150 |
| abstract_inverted_index.typical | 105 |
| abstract_inverted_index.Tolerant | 8 |
| abstract_inverted_index.actuator | 63, 80 |
| abstract_inverted_index.aircraft | 60, 106 |
| abstract_inverted_index.altitude | 107 |
| abstract_inverted_index.analysis | 138 |
| abstract_inverted_index.feedback | 81 |
| abstract_inverted_index.includes | 120 |
| abstract_inverted_index.inherent | 33 |
| abstract_inverted_index.performs | 136 |
| abstract_inverted_index.presence | 68 |
| abstract_inverted_index.presents | 41 |
| abstract_inverted_index.proposed | 73 |
| abstract_inverted_index.scenario | 119 |
| abstract_inverted_index.two-step | 152 |
| abstract_inverted_index.Detection | 1 |
| abstract_inverted_index.actuator, | 176 |
| abstract_inverted_index.aircraft. | 22 |
| abstract_inverted_index.autopilot | 109 |
| abstract_inverted_index.detection | 52, 154 |
| abstract_inverted_index.elevator, | 123 |
| abstract_inverted_index.operation | 19 |
| abstract_inverted_index.real-time | 77, 144 |
| abstract_inverted_index.reference | 50, 91 |
| abstract_inverted_index.scenario. | 116 |
| abstract_inverted_index.advantages | 85 |
| abstract_inverted_index.fixed-wing | 59 |
| abstract_inverted_index.instrument | 65, 177 |
| abstract_inverted_index.limitation | 34 |
| abstract_inverted_index.parameters | 78, 145 |
| abstract_inverted_index.predefined | 114 |
| abstract_inverted_index.simulation | 110 |
| abstract_inverted_index.accurately. | 188 |
| abstract_inverted_index.environment | 111, 187 |
| abstract_inverted_index.estimation. | 97 |
| abstract_inverted_index.identifying | 62 |
| abstract_inverted_index.implantable | 149 |
| abstract_inverted_index.implemented | 102 |
| abstract_inverted_index.operational | 28 |
| abstract_inverted_index.uncertainty. | 133 |
| abstract_inverted_index.disadvantages | 29 |
| abstract_inverted_index.distinguishes | 173 |
| abstract_inverted_index.environmental | 132 |
| abstract_inverted_index.uncertainties | 183 |
| abstract_inverted_index.Identification | 3 |
| abstract_inverted_index.identification | 54 |
| abstract_inverted_index.implementation | 45 |
| abstract_inverted_index.uncertainties. | 71 |
| abstract_inverted_index.identification. | 38, 164 |
| abstract_inverted_index.state-dependent | 143 |
| abstract_inverted_index.skin-implantable | 126 |
| abstract_inverted_index.state-independent | 147 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.19016615 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |