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针对线性时不变系统提出了一种基于故障跟踪估计器的故障诊断新方法。首先引入一个可调参数,称作虚拟故障,构建线性时不变系统的故障跟踪估计器。然后,设计迭代学习算法,在选取的优化周期内通过反复迭代学习运算来动态调节虚拟故障,使之估计出系统中实际发生的故障。该方法可以同时检测和估计出系统中发生的故障,而且和发生的故障类型无关。最后,在垂直升降飞行器的线性化模型上进行了仿真研究,仿真结果表明了所设计算法的可行性和有效性。
A new fault diagnosis method based on fault-tracking estimator is proposed for linear invariant systems. First, an adjustable parameter is introduced, called a virtual fault, to construct a fault-track estimator for invariant systems under linear conditions. Then, the iterative learning algorithm is designed to dynamically adjust the virtual faults in the selected optimization cycle through repeated iterative learning operations, so as to estimate the actual faults in the system. This method can detect and estimate the faults in the system at the same time, and has nothing to do with the type of the fault. Finally, the simulation research is carried out on the linearization model of vertical lift vehicle. The simulation results show the feasibility and effectiveness of the proposed algorithm.