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Adaptive prescribed performance tracking control for strict‐feedback nonlinear systems with zero dynamics
Author(s) -
Liu Cungen,
Wang Huanqing,
Liu Xiaoping,
Zhou Yucheng,
Lu Shouyin
Publication year - 2019
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.4739
Subject(s) - backstepping , control theory (sociology) , tracking error , bounded function , tracking (education) , nonlinear system , controller (irrigation) , zero (linguistics) , boundary (topology) , computer science , polynomial , function (biology) , adaptive control , mathematics , control (management) , artificial intelligence , psychology , mathematical analysis , pedagogy , linguistics , philosophy , physics , quantum mechanics , evolutionary biology , agronomy , biology
Summary This paper focuses on the adaptive tracking control problem for strict‐feedback nonlinear systems with zero dynamics via prescribed performance. Based on polynomial fitting, an adjustable performance function is firstly proposed, whose parameters can be adjusted in real time according to the tracking error. Furthermore, an adaptive prescribed performance tracking controller is constructed via the backstepping method, which guarantees that all the states in the closed‐loop system are bounded. Meanwhile, the output tracking error falls within an adjustable performance boundary and asymptotically converges to zero. Simulation comparison demonstrates the advantages of the developed controller as follows: (1) the parameters of the adjustable performance function are adjusted online according to the tracking errors for a faster convergent performance boundary; (2) the steady‐state performance of the system is further optimized simultaneously.