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A combined backstepping and dynamic surface control to adaptive fuzzy state‐feedback control
Author(s) -
Su Hang,
Zhang Weihai
Publication year - 2017
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2793
Subject(s) - backstepping , control theory (sociology) , fuzzy logic , fuzzy control system , controller (irrigation) , nonlinear system , linearization , adaptive neuro fuzzy inference system , adaptive control , feedback linearization , computer science , mathematics , control engineering , control (management) , engineering , artificial intelligence , physics , quantum mechanics , agronomy , biology
Summary This paper studies an adaptive fuzzy dynamic surface control for a class of nonlinear systems with fuzzy dead zone, unmodeled dynamics, dynamical disturbances, and unknown control gain functions. The unknown system functions are approximated by the Takagi‐Sugeno–type fuzzy logic systems. There are 3 main features for the presented systematic design scheme. First, by adopting an integrated method, a novel adaptive fuzzy controller is constructed for the nonlinear system with fuzzy dead zone. Second, only 3 online learning parameters need to be tuned, which significantly reduces the computation burden. Third, the possible controller singularity problem in some of the existing adaptive control methods with feedback linearization techniques can be avoided. On the basis of the backstepping technique and dynamic surface control, all the signals of the closed‐loop system are guaranteed to be semiglobally uniformly ultimately bounded. Finally, 2 simulation examples are provided to illustrate the effectiveness of the proposed scheme.