UIO-based diagnosis of aircraft engine control systems using scilab

Fault diagnosis is of significant importance to the robustness of aeroengine control systems. This paper makes use of full-order unknown input observers (UIOs) to facilitate the diagnosis of sensor/actuator faults in engine control systems. The built-in "ui-observer" function in Scilab, ho...

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description Fault diagnosis is of significant importance to the robustness of aeroengine control systems. This paper makes use of full-order unknown input observers (UIOs) to facilitate the diagnosis of sensor/actuator faults in engine control systems. The built-in "ui-observer" function in Scilab, however, can not give satisfying performance, in terms of observer realization. Hence we rewrite this UIO program in standard Scilab scripts and decouple the effect of unknown disturbances upon state estimation to improve the sensitivity to engine faults. An evaluation platform is created on the basis of the Xcos tool in a Simulink-like manner. All the above work is accomplished in the Scilab environment. Experimental results on an aircraft turbofan engine demonstrate that the suggested UIO diagnostic method has good anti-disturbance ability and can effectively detect and isolate sensor/actuator faults under various fault conditions.
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subjects Actuators
aircraft engine simulation
Aircraft propulsion
Engines
fault detection
fault diagnosis
Mathematical model
Robustness
UIO
Vectors
Xcos
title UIO-based diagnosis of aircraft engine control systems using scilab
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