UIO-based diagnosis of aircraft engine control systems using scilab

Y. Liu, Daoliang Tan, Ai He, Xi Wang
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引用次数: 1

Abstract

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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基于ui的飞机发动机控制系统scilab诊断
故障诊断对航空发动机控制系统的鲁棒性具有重要意义。本文利用全阶未知输入观测器(UIOs)对发动机控制系统中的传感器/执行器故障进行诊断。然而,Scilab中内置的“ui-observer”函数在观察者实现方面并不能给出令人满意的性能。因此,我们用标准的Scilab脚本重写了该UIO程序,并解耦了未知干扰对状态估计的影响,以提高对发动机故障的灵敏度。在Xcos工具的基础上,以类似simulink的方式创建了一个评估平台。以上工作均在Scilab环境下完成。在某型飞机涡扇发动机上的实验结果表明,所提出的UIO诊断方法具有良好的抗干扰能力,可以在各种故障条件下有效地检测和隔离传感器/执行器故障。
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