AUV fault detection using model based observer residuals
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- Publication date
- 1998-06-01 00:00:00
- Topics
- Adaptive control systems
- Publisher
- Monterey, California. Naval Postgraduate School
- Collection
- navalpostgraduateschoollibrary; fedlink
- Language
- English
In order for the Navy's next generation Unmanned Undersea Vehicles to be more robust to software/hardware faults, on-line failure detection and resolution is needed. Typically, fault detection methods include limits and trends analysis, model free, and model based techniques. Here, model based observers are proposed for the detection of fault induced dynamic signals in the diving, steering, and roll control systems. Such automatic fault detection systems were designed and implemented in a Simulink model of the \"21UUV.\" in the course of conducting simulations with the model, numerous vehicle behaviors were studied and detection response was verified. In addition, the model based observer residuals may be designed to distinguish actuator faults from wave disturbances and fin faults from maneuvering responses
- Addeddate
- 2020-11-19 05:44:08
- Advisor
- Healey, Anthony J.
- Degree_discipline
- Mechanical Engineering
- Degree_grantor
- Naval Postgraduate School
- Degree_level
- Masters
Professional Degree
- Degree_name
- M.S. in Mechanical Engineering
Degree of Mechanical Engineer
- Distributionstatement
- Approved for public release; distribution is unlimited.
- Dspace_note
- Note, the Item of Record as published can be found at https://hdl.handle.net/10945/8018.
- Foldoutcount
- 0
- Identifier
- auvfaultdetectio109458018
- Identifier-ark
- ark:/13960/t2f862115
- Identifier_handle
- 10945/8018
- Item_source
- dspace
- Ocr
- tesseract 4.1.1
- Ocr_detected_lang
- en
- Ocr_detected_lang_conf
- 1.0000
- Ocr_detected_script
- Latin
- Ocr_detected_script_conf
- 0.9426
- Ocr_module_version
- 0.0.10
- Ocr_parameters
- -l eng
- Orig_md5
- fd20438a3ab9a896d84c54e3362afb9a
- Page_number_confidence
- 73.61
- Pages
- 145
- Ppi
- 600
- Scanner
- Internet Archive Python library 1.8.1
- Service
- Lieutenant, United States Navy
- Type
- Thesis
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