Neural network and fuzzy logic approach to aircraft reconfigurable control design

Author

Chiang, Chi-Yuan ; Youssef, Hussein M.

Author_Institution

Dept. of Aerosp. Eng., Univ. of Southern California, Los Angeles, CA, USA

Volume

5

fYear

1995

fDate

21-23 Jun 1995

Firstpage

3505

Abstract

Modern aircraft systems require advanced onboard fault detection, isolation and reconfiguration (FDIR) in order to maintain its performance. Current FDIR designs are subject to uncertainty, nonlinearity, and complexity, leading to high false alarm rate and inaccurate feedback control. Recently, the emergence of neural fuzzy technology has generated a great deal of interest in system learning and control. In this paper, we synthesize a FDIR, scheme by combining neural network method with fuzzy logic concept and show the simulation results by using the nonlinear F-16 aircraft model

Keywords

aircraft control; control system synthesis; fault diagnosis; fuzzy control; fuzzy logic; intelligent control; learning systems; neural nets; neurocontrollers; aircraft reconfigurable control; fault detection; fault isolation; fuzzy control; fuzzy logic; neural network; nonlinear F-16 aircraft model; nonlinearity; system learning; uncertainty; Aircraft; Control systems; Fault detection; Feedback control; Fuzzy control; Fuzzy logic; Fuzzy systems; Isolation technology; Neural networks; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, Proceedings of the 1995

Conference_Location

Seattle, WA

Print_ISBN

0-7803-2445-5

Type

conf

DOI

10.1109/ACC.1995.533788

Filename

533788