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Adaptive actuator failure compensation for a class of nonlinear systems with full state constraints
Author(s) -
Ouyang Hupo,
Lin Yan
Publication year - 2020
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.5337
Subject(s) - control theory (sociology) , actuator , nonlinear system , tracking error , compensation (psychology) , bounded function , computer science , lyapunov function , scheme (mathematics) , state (computer science) , class (philosophy) , backstepping , set (abstract data type) , adaptive control , mathematics , control (management) , algorithm , artificial intelligence , psychoanalysis , mathematical analysis , psychology , physics , quantum mechanics , programming language
In this article, an adaptive compensation scheme is proposed for controlling a class of Brunovsky form systems with unknown parameters and possible actuator failures such that the full state constraints can be achieved. Compared with the previous research, the main advantage of the scheme is that by selecting a set of parameters related to the barrier Lyapunov functions, virtual control signals can be constrained within required boundaries. As a result, the full state constraints and tracking performance constraints can be achieved simultaneously even in the presence of actuator failures. It is shown that with this scheme, all the closed‐loop signals are bounded and the tracking error converges to a residue set that can be made arbitrarily small