Finite-Time Adaptive Control for a Class of Nonlinear Systems With Nonstrict Feedback Structure

This paper focuses on finite-time adaptive neural tracking control for nonlinear systems in nonstrict feedback form. A semiglobal finite-time practical stability criterion is first proposed. Correspondingly, the finite-time adaptive neural control strategy is given by using this criterion. Unlike th...

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Bibliographic Details
Published inIEEE transactions on cybernetics Vol. 48; no. 10; pp. 2774 - 2782
Main Authors Sun, Yumei, Chen, Bing, Lin, Chong, Wang, Honghong
Format Journal Article
LanguageEnglish
Published United States IEEE 01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive control
Adaptive neural control
Adaptive systems
Artificial neural networks
Backstepping
Control stability
Control systems
Feedback
finite time tracking
Fuzzy control
Fuzzy logic
Neural networks
Nonlinear control
Nonlinear systems
nonstrict feedback structure
Stability criteria
Tracking control
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Summary:This paper focuses on finite-time adaptive neural tracking control for nonlinear systems in nonstrict feedback form. A semiglobal finite-time practical stability criterion is first proposed. Correspondingly, the finite-time adaptive neural control strategy is given by using this criterion. Unlike the existing results on adaptive neural/fuzzy control, the proposed adaptive neural controller guarantees that the tracking error converges to a sufficiently small domain around the origin in finite time, and other closed-loop signals are bounded. At last, two examples are used to test the validity of our results.
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ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2017.2749511