Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach

By: Ehsan Sobhani-Tehrani, Khashayar Khorasani

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Paperback | 22 June 2009

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Theincreasingcomplexityofspacevehiclessuchassatellites, andthecostreduction measures that have affected satellite operators are increasingly driving the need for more autonomy in satellite diagnostics and control systems. Current methods for detecting and correcting anomalies onboard the spacecraft as well as on the ground are primarily manual and labor intensive, and therefore, tend to be slow. Operators inspect telemetry data to determine the current satellite health. They use various statisticaltechniques andmodels, buttheanalysisandevaluation ofthelargevolume of data still require extensive human intervention and expertise that is prone to error. Furthermore, for spacecraft and most of these satellites, there can be potentially unduly long delays in round-trip communications between the ground station and the satellite. In this context, it is desirable to have onboard fault-diagnosis system that is capable of detecting, isolating, identifying or classifying faults in the system withouttheinvolvementandinterventionofoperators.Towardthisend, theprinciple goal here is to improve the ef?ciency, accuracy, and reliability of the trend analysis and diagnostics techniques through utilization of intelligent-based and hybrid-based methodologies.

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Introduction	p. 1
Statement of the Work	p. 1
Motivation of the Work	p. 3
Objectives of the Research	p. 8
Literature Review	p. 8
Proposed Fault Diagnosis Scheme	p. 14
Contributions of the Monograph	p. 16
Outline of the Monograph	p. 18
Fault Detection and Diagnosis	p. 21
Problem Formulation	p. 21
Desired Attributes of a Fault Diagnosis System	p. 26
A Review of Analytical Redundancy-Based FDI Approaches	p. 28
Model-Based Approaches to FDI	p. 28
Computational Intelligence-Based Approaches to FDI	p. 38
Methodology Developed in This Monograph: Hybrid Approach to FDII	p. 44
Robustness of FDI to Uncertainties	p. 46
Conclusions	p. 48
Proposed FDII for Nonlinear Systems with Full-State Measurement	p. 51
Fault Modeling and Health Indicator Parameters	p. 52
FDII using Parameter Estimation	p. 56
Conventional Linear and Nonlinear Parameter Estimation	p. 58
Neural Network-Based Parameter Estimation	p. 60
FDII using Series-Parallel Architecture of Neural Parameter Estimators	p. 61
Weight Update Laws of the Series-Parallel Scheme	p. 63
FDI Decision Logic of the Series-Parallel Scheme	p. 65
Robust FDII Using Parallel Architecture of NPEs	p. 66
Weight Update Laws of the Robust Parallel Scheme	p. 68
Fault Isolation Policy of the Parallel Scheme	p. 68
Conclusions	p. 69
Proposed FDII for Nonlinear Systems with Partial State Measurement	p. 71
FDII Using the Series-Parallel Scheme Under Partial-State Measurements	p. 72
FDII Using the Parallel Scheme Under Partial-State Measurements	p. 74
Fault-Tolerant State Estimation	p. 75
State Estimation of Nonlinear Dynamical Systems	p. 77
Probabilistically Inspired Approaches to Nonlinear Filtering	p. 78
Statistically Inspired Approaches to Nonlinear Filtering	p. 80
Model-Based State Estimation	p. 81
Learning and Computational Intelligence-Based State Estimation	p. 82
Probabilistically Inspired Approaches to Neural Network-Based Filtering	p. 83
Statistically Inspired Approaches to Neural Network-Based Filtering	p. 85
Kalman Filter Structure-Preserving Neural State Estimator (NSE)	p. 88
Update Laws for the NSE: Recursive On-Line Backpropagation	p. 90
Conclusions	p. 96
Application to a Satellite's Attitude Control Subsystem	p. 99
Spacecraft Subsystems	p. 100
Satellite Attitude Control Subsystem (ACS)	p. 102
Fault Diagnosis in Satellite ACS	p. 102
Satellite Attitude Dynamics	p. 103
Mathematical Modeling of External Attitude Disturbances	p. 114
Attitude Control	p. 117
Three-Axis Active Attitude Control Design	p. 117
Simulation Results of 3-Axis Stabilized ACS	p. 118
Three-Axis Attitude Stabilization	p. 118
Characterization of Possible Fault Scenarios in Reaction Wheels	p. 130
Simulation Results for FDII with Full-State Measurements	p. 130
Simulation Results for FDII Using the Series-Parallel Scheme	p. 134
Robustness Analysis of the Series-Parallel FDII Scheme with respect to Measurement Noise	p. 149
Simulation Results for FDII Using the Parallel Scheme	p. 164
Robustness Analysis of the Parallel FDII Scheme with respect to Measurement Noise	p. 177
Simulation Results for FDII with Partial-State Measurement	p. 193
State Estimation Under Healthy Conditions	p. 194
State Estimation in Presence of Faults	p. 197
FDII Using Estimates of the Current from the NSE	p. 200
Conclusions	p. 215
Conclusions	p. 219
References	p. 225
Ordered Partial Derivatives	p. 235
Attitude Reference System and Coordinate Frames	p. 237
Extra Figures of FDII Results	p. 241
Index	p. 261
Table of Contents provided by Ingram. All Rights Reserved.

Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

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