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Adaptive fuzzy control for nonlinear uncertain pure‐feedback systems with full‐state and input constraints
Author(s) -
Jia Fujin,
Lu Junwei,
Li Yongmin
Publication year - 2021
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5511
Subject(s) - backstepping , control theory (sociology) , nonlinear system , constraint (computer aided design) , bounded function , tracking error , lyapunov function , computer science , state (computer science) , fuzzy logic , logarithm , mathematical optimization , mathematics , control (management) , adaptive control , algorithm , artificial intelligence , mathematical analysis , physics , geometry , quantum mechanics
This paper studies the full‐state and input constraints of uncertain nonlinear pure‐feedback systems. The radical constraint functions are proposed, which avoids the drawbacks of the barrier Lyapunov functions and the logarithmic constraint functions. At the same time, a control algorithm based on fuzzy control is proposed to avoid the "explosion of terms" problem of the backstepping method. In addition, this paper avoids an Assumption of nonaffine function, which reduces the conservatism and increases the applicability of the algorithm. This control algorithm is proposed so that all signals of the closed‐loop system are the semi‐globally uniformly ultimately bounded, and the tracking error converge to a small neighborhood of the origin, and all states and input of nonlinear pure‐feedback systems can be constrained. Finally, simulation results are provided to verify the effectiveness of the proposed approach.