Adaptive Fuzzy Control of Nonlinear Systems With Unmodeled Dynamics and Input Saturation Using Small-Gain Approach

This paper investigates the problem of adaptive fuzzy state-feedback control for a category of single-input and single-output nonlinear systems in nonstrict-feedback form. Unmodeled dynamics and input constraint are considered in the system. Fuzzy logic systems are employed to identify unknown nonli...

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Published inIEEE transactions on systems, man, and cybernetics. Systems Vol. 47; no. 8; pp. 1979 - 1989
Main Authors Zhou, Qi, Li, Hongyi, Wu, Chengwei, Wang, Lijie, Ahn, Choon Ki
Format Journal Article
LanguageEnglish
Published New York IEEE 01.08.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN2168-2216
2168-2232
DOI10.1109/TSMC.2016.2586108

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Summary:This paper investigates the problem of adaptive fuzzy state-feedback control for a category of single-input and single-output nonlinear systems in nonstrict-feedback form. Unmodeled dynamics and input constraint are considered in the system. Fuzzy logic systems are employed to identify unknown nonlinear characteristics existing in systems. An appropriate Lyapunov function is chosen to ensure unmodeled dynamics to be input-to-state practically stable. A smooth function is introduced to tackle input saturation. In order to overcome the difficulty of controller design for nonstrict-feedback system in backstepping design process, a variables separation method is introduced. Moreover, based on small-gain technique, an adaptive fuzzy controller is designed to guarantee all the signals of the resulting closed-loop system to be bounded. Finally, two illustrative examples are given to validate the effectiveness of the new design techniques.
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ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2016.2586108