文献类型：期刊文献

英文题名：A New Method to Fault Diagnosis for a Class of Nonlinear Systems

作者：Liu Jun[1,2];Yu Jinshou[1];Yan Bingyong[1]

机构：[1]E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]Shanghai Dianji Univ, Sch Elect Engn, Shanghai 200240, Peoples R China

年份：2011

卷号：20

期号：2

起止页码：217

外文期刊名：CHINESE JOURNAL OF ELECTRONICS

收录：;EI(收录号：20112414049862);WOS:【SCI-EXPANDED(收录号:WOS:000291178100005)】；

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).

语种：英文

外文关键词：Fault detection and identification; Nonlinear systems; Predictive control; Iterative learning control; Fault tracking approximator

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.