Adaptive estimation of component faults and actuator faults for nonlinear one‐sided Lipschitz systems

Many existing aircraft engine diagnostic methods are based on linearized engine models. However, the dynamics of aircraft engines are highly nonlinear and rapidly changing. Future engine health management designs will benefit from new methods that are directly based on intrinsic nonlinearities of the engine dynamics. In this paper, a fault detection and isolation (FDI) method is developed for aircraft engines by utilizing nonlinear adaptive estimation and nonlinear observer techniques. Engine sensor faults, actuator faults and component faults are considered under one unified nonlinear framework. The fault diagnosis architecture consists of a fault detection estimator and a bank of nonlinear fault isolation estimators. The fault detection estimator is used for detecting the occurrence of a fault, while the bank of fault isolation estimators is employed to determine the particular fault type or location after fault detection. Each isolation estimator is designed based on the functional structure of a particular fault type under consideration. Specifically, adaptive estimation techniques are used for designing the isolation estimators for engine component faults and actuator faults, while nonlinear observer techniques are used for designing the isolation estimators for sensor faults. The FDI architecture has been integrated with the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) engine model developed by NASA researchers in recent years. The engine model is a realistic representation of the nonlinear aero thermal dynamics of a 90,000-pound thrust class turbofan engine with high-bypass ratio and a two-spool configuration. Representative simulation results and comparative studies are shown to verify the effectiveness of the nonlinear FDI method.

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A Unified Nonlinear Adaptive Approach for Detection and Isolation of Engine Faults

Volume 3: Controls, Diagnostics and Instrumentation; Cycle Innovations; Marine ◽

10.1115/gt2010-22642 ◽

2010 ◽

Cited By ~ 6

Author(s):

Liang Tang ◽

Xiaodong Zhang ◽

Jonathan A. DeCastro ◽

Luis Farfan-Ramos ◽

Donald L. Simon

Keyword(s):

Health Management ◽

System Development ◽

Aircraft Engine ◽

Fault Detection And Isolation ◽

Specific Response ◽

Sensor Faults ◽

Actuator Faults ◽

Unified Framework ◽

Adaptive Estimator ◽

Component Faults

A challenging problem in aircraft engine health management (EHM) system development is to detect and isolate faults in system components (i.e., compressor, turbine), actuators, and sensors. Existing nonlinear EHM methods often deal with component faults, actuator faults, and sensor faults separately, which may potentially lead to incorrect diagnostic decisions and unnecessary maintenance. Therefore, it would be ideal to address sensor faults, actuator faults, and component faults under one unified framework. This paper presents a systematic and unified nonlinear adaptive framework for detecting and isolating sensor faults, actuator faults, and component faults for aircraft engines. The fault detection and isolation (FDI) architecture consists of a parallel bank of nonlinear adaptive estimators. Adaptive thresholds are appropriately designed such that, in the presence of a particular fault, all components of the residual generated by the adaptive estimator corresponding to the actual fault type remain below their thresholds. If the faults are sufficiently different, then at least one component of the residual generated by each remaining adaptive estimator should exceed its threshold. Therefore, based on the specific response of the residuals, sensor faults, actuator faults, and component faults can be isolated. The effectiveness of the approach was evaluated using the NASA C-MAPSS turbofan engine model, and simulation results are presented.

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Robust Adaptive Switching Fault-Tolerant Control of a Class of Uncertain Systems against Actuator Faults

Mathematical Problems in Engineering ◽

10.1155/2013/852502 ◽

2013 ◽

Vol 2013 ◽

pp. 1-9 ◽

Cited By ~ 7

Author(s):

Xiao-Zheng Jin

Keyword(s):

Fault Tolerant ◽

Linear Time ◽

Adaptive Estimation ◽

Fault Tolerant Control ◽

Uncertain System ◽

Switching Function ◽

Actuator Faults ◽

Linear Time Invariant ◽

Robust Adaptive ◽

Linear Time Invariant Systems

This paper deals with the fault-tolerant control (FTC) problem for a class of linear time-invariant systems with time-varying actuator faults and uncertainties. For more general consideration, the faults and uncertainties are supposed to depend on the states of systems and unknown constant bounds. For the sake of eliminating the effects of such state-dependent faults and uncertainties automatically, a switching control strategy which is formulated by a sign function is designed to configure controller based on system’s states. And some adjustable control parameters are updated via designing adaptive laws. Based on the information from switching function and the adaptive estimation mechanism, the robust adaptive controllers are constructed to compensate for the effects of faults and uncertainties. Through Lyapunov functions and adaptive schemes, the asymptotic stability of the resulting adaptive FTC uncertain system can be achieved. The effectiveness of the proposed design is illustrated via a rocket fairing structural-acoustic model.

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