Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/37624
Title: Knowledge-based automatic fault detection in flight control system
Authors: Lo, CH
Fung, EHK
Wong, YK 
Keywords: Control systems
Flaw detection
Flight
Issue Date: 2007
Source: Proceedings of the ASME 2007 International Mechanical Engineering Congress and Exposition, Seattle, Washington, USA, November 11–15, 2007, v. 9, paper no. IMECE2007-41495, p. 605-610 (CD-ROM) How to cite?
Abstract: There are various possible failures, like, actuator, sensor, or structural, which can occur on a sophisticated modern aircraft. In certain situations the need for an automatic fault detection system provides additional information about the status of the aircraft to assist pilots to compensate for failures. In this paper, we develop an intelligent technique based on fuzzy-genetic algorithm for automatically detecting failures in flight control system. The fuzzy-genetic algorithm is proposed to construct the automatic fault detection system for monitoring aircraft behaviors. Fuzzy system is employed to estimates the times and types of actuator failure. Genetic algorithms are used to generate an optimal fuzzy rule set based on the training data. The optimization capability of genetic algorithms provides and efficient and effective way to generate optimal fuzzy rules. Different types of actuator failure can be detected by the fuzzy-genetic algorithm based automatic fault detection system after tuning its rule table. Simulations with different actuator failures of the non-linear F-16 aircraft model are conducted to appraise the performance of the proposed automatic fault detection system.
URI: http://hdl.handle.net/10397/37624
ISBN: 0-7918-4303-3
0-7918-3812-9 (E-ISBN)
DOI: 10.1115/IMECE2007-41495
Appears in Collections:Conference Paper

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