DocumentCode :
1799331
Title :
Adaptive fault identification for a class of nonlinear dynamic systems
Author :
Li-Bing Wu ; Dan Ye ; Xin-Gang Zhao
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear :
2014
fDate :
9-12 Dec. 2014
Firstpage :
1
Lastpage :
6
Abstract :
This paper is concerned with the diagnosis problem of actuator faults for a class of nonlinear systems. It is assumed that the upper bound of the Lipschtiz constant of the nonlinearity in the faulty system is unknown. Then, a new nonlinear observer for fault diagnosis based on an adaptive estimator is proposed. Moreover, by making use of the designed adaptive observer with on-line update control law without σ-modification condition to approximate the faulty system, it is proved that the estimate error of the adaptive control parameter, the output observation error and the error between the system fault and the corresponding estimate value are uniformly ultimately bounded via Lyapunov stability analysis. Finally, simulation examples are provided to illustrate the efficiency of the proposed fault identification approach.
Keywords :
Lyapunov methods; adaptive control; adaptive estimation; fault diagnosis; nonlinear dynamical systems; observers; stability; Lipschtiz constant; Lyapunov stability analysis; actuator faults; adaptive control parameter; adaptive estimator; adaptive fault identification; adaptive observer; diagnosis problem; estimate error; fault diagnosis; faulty system nonlinearity; nonlinear dynamic systems; nonlinear observer; online update control law; output observation error; upper bound; Adaptive systems; Educational institutions; Fault detection; Fault diagnosis; Nonlinear systems; Observers; Upper bound;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/ADPRL.2014.7010635
Filename :
7010635
Link To Document :
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