Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control
This thesis focuses on the development of two efficient sequential fuzzy neural algorithms. The first algorithm is named as Sequential Adaptive Fuzzy Inference System where the number of fuzzy rules is determined automatically according to the learning procedure and the parameters in the existing fu...
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| Format: | Thesis |
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2008
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| Online Access: | https://hdl.handle.net/10356/3507 |
| _version_ | 1826113871930195968 |
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| author | Rong, Haijun |
| author2 | Narasimhan Sundararajan |
| author_facet | Narasimhan Sundararajan Rong, Haijun |
| author_sort | Rong, Haijun |
| collection | NTU |
| description | This thesis focuses on the development of two efficient sequential fuzzy neural algorithms. The first algorithm is named as Sequential Adaptive Fuzzy Inference System where the number of fuzzy rules is determined automatically according to the learning procedure and the parameters in the existing fuzzy rules are modified. The second algorithm is called as On-line, Sequential, Fuzzy Extreme Learning Machine where the parameters for the fuzzy rules are updated at an extremely high speed. Besides based on the two new fuzzy neural algorithms, two adaptive, fault-tolerant, fuzzy control strategies are developed in this thesis for a high performance fighter automatic landing problem under the failures of stuck control surfaces and severe winds. |
| first_indexed | 2024-10-01T03:30:18Z |
| format | Thesis |
| id | ntu-10356/3507 |
| institution | Nanyang Technological University |
| last_indexed | 2024-10-01T03:30:18Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | ntu-10356/35072023-07-04T17:33:32Z Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control Rong, Haijun Narasimhan Sundararajan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Aeronautical engineering::Air navigation This thesis focuses on the development of two efficient sequential fuzzy neural algorithms. The first algorithm is named as Sequential Adaptive Fuzzy Inference System where the number of fuzzy rules is determined automatically according to the learning procedure and the parameters in the existing fuzzy rules are modified. The second algorithm is called as On-line, Sequential, Fuzzy Extreme Learning Machine where the parameters for the fuzzy rules are updated at an extremely high speed. Besides based on the two new fuzzy neural algorithms, two adaptive, fault-tolerant, fuzzy control strategies are developed in this thesis for a high performance fighter automatic landing problem under the failures of stuck control surfaces and severe winds. DOCTOR OF PHILOSOPHY (EEE) 2008-09-17T09:31:12Z 2008-09-17T09:31:12Z 2007 2007 Thesis Rong, H. (2007).Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/3507 10.32657/10356/3507 Nanyang Technological University application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Aeronautical engineering::Air navigation Rong, Haijun Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control |
| title | Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control |
| title_full | Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control |
| title_fullStr | Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control |
| title_full_unstemmed | Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control |
| title_short | Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control |
| title_sort | efficient sequential fuzzy neural algorithms for aircraft fault tolerant control |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Aeronautical engineering::Air navigation |
| url | https://hdl.handle.net/10356/3507 |
| work_keys_str_mv | AT ronghaijun efficientsequentialfuzzyneuralalgorithmsforaircraftfaulttolerantcontrol |