Robust Fault Identification of Turbofan Engines Sensors Based on Fractional-Order Integral Sliding Mode Observer

Abstract

This paper presents a robust fault identification scheme based on fractional-order integral sliding mode observer (FOISMO) for turbofan engine sensors with uncertainties. The equilibrium manifold expansion (EME) model is introduced due to its simplicity and accuracy for nonlinear system. A fractional-order integral sliding mode observer is designed to reconstruct faults on sensors, in which the fractional-order integral sliding surface guarantees the fast convergence of reconstruction. The observer parameters is selected according to L2 gain theory in order to minimize the effect of uncertainties on the fault reconstruction signal. Simulations in Matlab/Simulink show high reconstruction accuracy of the proposed method despite the present of uncertainties.

A Corrected Equilibrium Manifold Expansion Model for Gas Turbine System Simulation and Control

“…Equilibrium manifold expansion (EME) model has gained more and more attention because of its simplicity and clear structure. The EME model is an approximate nonlinear model developed from the Jacobian Linearization model [4], which has been widely used in the field of system simulation [5,6], system control [7,8], and fault diagnosis [9]. It is generally known that the Jacobian linearization model is only valid near its equilibrium point, but the EME model is a global nonlinear model, which can deal with the entire range of operation conditions [10].…”