Premium
Small‐gain technique‐based adaptive fuzzy command filtered control for uncertain nonlinear systems with unmodeled dynamics and disturbances
Author(s) -
Li Yulin,
Xu Ning,
Niu Ben,
Chang Yi,
Zhao Jinfeng,
Zhao Xudong
Publication year - 2021
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.3283
Subject(s) - control theory (sociology) , backstepping , fuzzy logic , nonlinear system , fuzzy control system , controller (irrigation) , tracking error , observer (physics) , bounded function , adaptive control , stability (learning theory) , compensation (psychology) , filter (signal processing) , computer science , mathematics , control (management) , artificial intelligence , psychology , mathematical analysis , physics , quantum mechanics , machine learning , psychoanalysis , agronomy , computer vision , biology
Summary This article studies the adaptive tracking control problem for a class of uncertain nonlinear systems with unmodeled dynamics and disturbances. First, a fuzzy state observer is established to estimate unmeasurable states. To overcome the problem of calculating explosion caused by the repeated differentiation of the virtual control signals, the command filter with a compensation mechanism is applied to the controller design procedure. Meanwhile, with the help of the fuzzy logic systems and the backstepping technique, an adaptive fuzzy control scheme is proposed, which guarantees that all signals in the closed‐loop systems are bounded, and the tracking error can converge to a small region around the origin. Furthermore, the stability of the systems is proven to be input‐to‐state practically stable based on the small‐gain theorem. Finally, a simulation example verifies the effectiveness of the proposed control approach.