Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/3507
Title: Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control
Authors: Rong, Haijun
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
DRNTU::Engineering::Aeronautical engineering::Air navigation
Issue Date: 2007
Source: Rong, H. (2007).Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: 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.
URI: https://hdl.handle.net/10356/3507
DOI: 10.32657/10356/3507
Rights: Nanyang Technological University
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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