Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs

ABSTRACT Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs Ling Ma Fault Detection and Diagnosis (FDD), as the central part of a Fault Tolerant Control System (FTCS), detects and diagnoses the source and the magnitude of a fault when a fa...

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Main Author: Ma, Ling
Format: Others
Published: 2011
Online Access:http://spectrum.library.concordia.ca/7466/1/MA_MASc_S20..pdf
Ma, Ling <http://spectrum.library.concordia.ca/view/creators/Ma=3ALing=3A=3A.html> (2011) Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs. Masters thesis, Concordia University.
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spelling ndltd-LACETR-oai-collectionscanada.gc.ca-QMG.74662013-10-22T03:45:05Z Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs Ma, Ling ABSTRACT Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs Ling Ma Fault Detection and Diagnosis (FDD), as the central part of a Fault Tolerant Control System (FTCS), detects and diagnoses the source and the magnitude of a fault when a fault/failure occurs either in an actuator, sensor or in the system itself. This thesis work develops an applicable procedure for a FDD scheme to both fixed-wing and rotary-wing UAVs (Unmanned Aerial Vehicles) in the discrete-time stochastic domain based on the Kalman filter techniques. In particular, the proposed techniques are developed in highly nonlinear and 6 degree-of-freedom equations of Matlab/Simulink simulation environment for a quad-rotor helicopter UAV, a Boeing 747, and a NASA Generic Transport Model (GTM) fixed-wing UAV. A key development in this thesis is that an Adaptive Two-Stage Extended Kalman Filter (ATSEKF) algorithm and a Dual Unscented Kalman Filter (DUKF) algorithm are applied for simultaneous states and fault parameters estimation of these UAVs. The statistical decision-making techniques for fault detection and diagnosis are also discussed in the presence of partial faults in the UAVs. The measured system outputs and control signals are used as inputs of the ATSEKF and DUKF, and the estimated states and parameters are used for comparison and analysis in the fault detection and diagnosis. The simulation results show that the effectiveness and performance of ATSEKF and DUKF for the purpose of fault detection and diagnosis of both fixed- and rotary-wing UAVs are satisfactory. 2011-01-12 Thesis NonPeerReviewed application/pdf http://spectrum.library.concordia.ca/7466/1/MA_MASc_S20..pdf Ma, Ling <http://spectrum.library.concordia.ca/view/creators/Ma=3ALing=3A=3A.html> (2011) Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs. Masters thesis, Concordia University. http://spectrum.library.concordia.ca/7466/
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description ABSTRACT Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs Ling Ma Fault Detection and Diagnosis (FDD), as the central part of a Fault Tolerant Control System (FTCS), detects and diagnoses the source and the magnitude of a fault when a fault/failure occurs either in an actuator, sensor or in the system itself. This thesis work develops an applicable procedure for a FDD scheme to both fixed-wing and rotary-wing UAVs (Unmanned Aerial Vehicles) in the discrete-time stochastic domain based on the Kalman filter techniques. In particular, the proposed techniques are developed in highly nonlinear and 6 degree-of-freedom equations of Matlab/Simulink simulation environment for a quad-rotor helicopter UAV, a Boeing 747, and a NASA Generic Transport Model (GTM) fixed-wing UAV. A key development in this thesis is that an Adaptive Two-Stage Extended Kalman Filter (ATSEKF) algorithm and a Dual Unscented Kalman Filter (DUKF) algorithm are applied for simultaneous states and fault parameters estimation of these UAVs. The statistical decision-making techniques for fault detection and diagnosis are also discussed in the presence of partial faults in the UAVs. The measured system outputs and control signals are used as inputs of the ATSEKF and DUKF, and the estimated states and parameters are used for comparison and analysis in the fault detection and diagnosis. The simulation results show that the effectiveness and performance of ATSEKF and DUKF for the purpose of fault detection and diagnosis of both fixed- and rotary-wing UAVs are satisfactory.
author Ma, Ling
spellingShingle Ma, Ling
Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs
author_facet Ma, Ling
author_sort Ma, Ling
title Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs
title_short Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs
title_full Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs
title_fullStr Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs
title_full_unstemmed Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs
title_sort development of fault detection and diagnosis techniques with applications to fixed-wing and rotary-wing uavs
publishDate 2011
url http://spectrum.library.concordia.ca/7466/1/MA_MASc_S20..pdf
Ma, Ling <http://spectrum.library.concordia.ca/view/creators/Ma=3ALing=3A=3A.html> (2011) Development of Fault Detection and Diagnosis Techniques with Applications to Fixed-wing and Rotary-wing UAVs. Masters thesis, Concordia University.
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