Open AccessObserver‐based adaptive fault estimation and fault‐tolerant tracking control for a class of uncertain nonlinear systems
Author(s) -
Wu Yang,
Zhang Guoshan,
Wu Libing
Publication year - 2021
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/cth2.12021
Subject(s) - control theory (sociology) , backstepping , observer (physics) , nonlinear system , fuzzy logic , fault tolerance , fault (geology) , tracking error , computer science , process (computing) , controller (irrigation) , fuzzy control system , fault detection and isolation , bounded function , control engineering , adaptive control , engineering , mathematics , control (management) , artificial intelligence , actuator , distributed computing , physics , quantum mechanics , seismology , geology , mathematical analysis , agronomy , biology , operating system
This paper considers the problem of adaptive fault estimation and fault‐tolerant tracking control for a class of uncertain nonlinear systems with model uncertainty and process fault. By utilising the approximation abilities of fuzzy logic systems, a novel fault estimation fuzzy observer is designed to estimate the unmeasured states, nonlinear functions and process fault. Based on backstepping technologies, a adaptive fuzzy fault‐tolerant controller with the adaptive updated laws is established, which can not only ensure the prescribed tracking performances, but also effectively compensate the process fault. It is proved that all the closed‐loop signals of systems are uniformly ultimately bounded and the tracking errors can constrain to the prescribed bounds. Finally, simulation results can verify the efficiency of the proposed approach.