Data-driven adaptive fault diagnosis method for nonlinear systems
GUO Kaipu
LI Hongfei
FAN Lingling
JI Honghai
Abstract：For a class of discrete time nonlinear systems,the simultaneous online estimation of actuator and sensor faults was realized based on the data-driven adaptive filtering for fault diagnosis(DDAF-FD)method.Firstly,the dynamic linearization technique was used to transform the nonlinear system into a quasi-linear model,which solved the problem that the nonlinear system was difficult to model accurately.Secondly,only using system I/O data,a data-driven adaptive fault diagnosis method was designed under the framework of data-driven filtering and recursive least squares algorithm,and the real-time accurate estimation of the two fault failure factors was realized.The stability of the proposed method was proved by Lyapunov method.The effectiveness of the proposed method was verified by the comparison of simulation experiment.
Keywords：data-driven filteringdynamic linearizationfault diagnosisleast squares algorithm
Publication Date：2023-12-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 134-141 )