A Nonlinear Version of The Generalized Likelihood Ratio Test

摘要：

　　In this paper,a new version of the generalized likelihood ratio(GLR)test is proposed to deal with the fault diagnosis problem in nonlinear systems.The unscented Kalman filter(UKF)is utilized for state estimation and innovation generation.The fault signatures used in the hypotheses test are pre-computed by running the fault model and the nominal model simultaneously based on the state estimations.In such a way the intolerable computational problem,which arise from applying a bank of nonlinear filters,is solved.Further more,the fault isolation problem as well as the fault estimation problem of the non-abrupt fault is discussed based on the nonlinear GLR approach.The simulation study of a longitudinal aircraft model is utilized to show the effectiveness of the proposed method.

关键词： generalized likelihood ratio (GLR) UKF Nonlinear systems Fault diagnosis

作者: LIU Hai ZHONG Maiying

作者单位: School of Instrument Science & Opto-electronics Engineering,Beihang University,Beijing,100191,P.R.China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 3175-3180

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）