航空发动机滑模容错控制技术研究

发布时间：2018-08-07 09:02

【摘要】：航空发动机是一个非线性、强耦合且具有极大不确定性的复杂系统,所以必须要有先进的控制技术来保证发动机安全、稳定、高效的运行。又因为发动机经常处于高速、高温、高压以及强振动的恶劣工作环境之中,发生故障的频率很高,所以设计具有容错功能的控制系统对于提高发动机工作的可靠性与安全性具有很大的意义。本文主要针对滑模理论应用于航空发动机的故障诊断与容错控制技术进行了初步的研究。首先,以某型双轴混排加力式涡扇发动机为研究对象,利用GasTurb 10提供的设计点数据及各截面性能参数,依据发动机的各个部件在工作过程中所遵循的气动、热力学定律,采用解析法建立了涡扇发动机的动静态数学模型。并且利用最小二乘拟合法建立了适维的状态空间模型,为下文滑模控制器与滑模观测器的设计奠定了基础。接着根据经典滑模控制理论,针对基于符号函数的趋近律法会导致抖振现象的问题,改进了原有的趋近律,分别用饱和函数以及连续函数做替换优化,利用极点配置法设计了滑模控制器并进行了仿真研究。仿真结果显示,优化后的趋近律法能减小超调并且减小稳态误差,且能有效的削弱抖振。然后针对滑模观测器理论应用于航空发动机的气路部件故障诊断进行了研究,先通过设计Utkin滑模观测器来达到准确估计系统状态的效果,并且研究了滑模观测器的稳定性,以及满足匹配条件时系统的抗干扰性能。在此基础之上,针对气路部件故障设计了增广的滑模观测器,利用线性矩阵不等式的方法,实现了对发动机气路部件健康参数蜕化的估计。并且利用滑模观测器组的方法可以将发动机气路部件故障与传感器故障进行有效的隔离与区分,实现了发动机多重故障的联合诊断。通过将滑模观测器的估计效果与卡尔曼滤波器进行对比可知,滑模观测器诊断估计效果更好,鲁棒性更好。最后综合了滑模控制器理论和滑模观测器理论,实现了航空发动机传感器故障的容错控制与仿真,仿真结果表明,设计的容错控制系统可以及时诊断并隔离传感器故障,并能准确地重构故障信号并反馈给滑模控制器,达到了容错控制的目的。
[Abstract]:Aero-engine is a complex system with nonlinear, strong coupling and great uncertainty, so it is necessary to have advanced control technology to ensure the safe, stable and efficient operation of the engine. And because the engine is often in the harsh working environment of high speed, high temperature, high pressure and strong vibration, the frequency of failure is very high. Therefore, the design of fault-tolerant control system is of great significance to improve the reliability and safety of engine work. In this paper, the application of sliding mode theory in fault diagnosis and fault-tolerant control of aeroengine is studied. First of all, based on the design point data provided by GasTurb 10 and the performance parameters of each section of the turbofan engine, the aerodynamic and thermodynamic laws followed by the various components of the engine during the working process are taken as the research object. The dynamic and static mathematical model of turbofan engine is established by analytical method. The state space model with proper dimension is established by using the least square fitting method, which lays a foundation for the design of sliding mode controller and sliding mode observer. Then, according to the classical sliding mode control theory, aiming at the problem that the law of approach based on sign function will lead to buffeting, the original approach law is improved, and the saturation function and continuous function are used to replace and optimize, respectively. The sliding mode controller is designed by pole assignment method and simulated. Simulation results show that the optimized approach law can reduce overshoot and steady-state error, and can effectively weaken buffeting. Then, the application of sliding mode observer theory to aero-engine gas path fault diagnosis is studied. Firstly, the Utkin sliding mode observer is designed to accurately estimate the system state, and the stability of the sliding mode observer is studied. And the anti-interference performance of the system when the matching condition is satisfied. On the basis of this, an augmented sliding mode observer is designed for the fault of gas path components, and the method of linear matrix inequality (LMI) is used to estimate the degradation of the health parameters of the gas path components of the engine. And the sliding mode observer group can effectively isolate and distinguish the fault of engine gas path and sensor, and realize the joint diagnosis of multiple faults of engine. By comparing the estimation effect of sliding mode observer with Kalman filter, it can be seen that the estimation effect of sliding mode observer is better and the robustness is better. Finally, the theory of sliding mode controller and the theory of sliding mode observer are integrated to realize the fault tolerant control and simulation of aero-engine sensor fault. The simulation results show that the designed fault tolerant control system can diagnose and isolate sensor faults in time. The fault signal can be reconstructed accurately and fed back to the sliding mode controller to achieve the purpose of fault-tolerant control.
【学位授予单位】：南京航空航天大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：V233.7

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