A New Method to Fault Nonlinear Diagnosis for a Class of Systems  

作　　者：LIU Jun YU Jinshou YAN Bingyong 

机构地区：[1]School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China [2]School of Electrical Engineering, Shanghai Dianji University, Shanghai 200240, China

出　　处：《Chinese Journal of Electronics》2011年第2期217-222,共6页电子学报（英文版）

基　　金：This work is supported by the National Natural Science Foundation of China （No.60434020, No.60772006）, Leading Academic Discipline Project of Shanghai Municipal Education Commission （No.J51901）.

摘　　要：Many of large-scale systems have embraced a number of highly nonlinear dynamic behaviours and thus pose an operational challenge for fault diagnosis schemes based on a linear perturbation model. In this paper, we proposed a novel Fault detection and identification （FDI） scheme for a class of nonlinear systems. The scheme seeks to design an on-line approximator with an adjustable parameter, which is the so-called Fault tracking approximator （FTA）. Motivated by the success of predictive control and iterative learning control theory, a stable iterative algorithm is also exploited to update the adjustable parameter in the FTA. The main progress made in this work is that the proposed approach has enabled a leading-edge feature of detecting and identifying the fault shape and fault magnitude simultaneously. The proposed approach is illustrated to be very robust and effective in numerical simulation experiment of this paper.

关 键 词：Fault detection and identification Nonlinear systems Predictive control Iterative learning control Fault tracking approximator. 

分 类 号：TP271[自动化与计算机技术—检测技术与自动化装置] TP393[自动化与计算机技术—控制科学与工程]