Robust fault estimation for T-S fuzzy systems with unmeasurable premise variables and random time delays

This paper studies the problem of actuator fault estimation (FE) for a class of T-S fuzzy systems with unmeasurable premise variables, which is subject to random time-varying delay and norm-bounded external disturbance. By taking the unmeasurable premise variables and actuator fault as auxiliary dis...

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Bibliographic Details
Published inChinese Control and Decision Conference pp. 4382 - 4388
Main Authors Chao Sun, Fuli Wang, Xiqin He, Suhuan Yi
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2017
Subjects
Actuators
Delay effects
Delays
fault estimation
Fuzzy systems
Iron
Observers
T-S fuzzy systems
time delays
unmeasurable premise variables
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ISSN1948-9447
DOI10.1109/CCDC.2017.7979269

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Summary:This paper studies the problem of actuator fault estimation (FE) for a class of T-S fuzzy systems with unmeasurable premise variables, which is subject to random time-varying delay and norm-bounded external disturbance. By taking the unmeasurable premise variables and actuator fault as auxiliary disturbance signal, the robust FE observer based on n-steps iterative learning algorithm is constructed to guarantee the error dynamic system to be asymptotically stable with a prescribed H ∞ performance. An improved sufficient condition of such observer is presented in terms of linear matrix inequality, which includes the information of the upper and lower bounds of time delay. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
ISSN:1948-9447
DOI:10.1109/CCDC.2017.7979269