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Integral barrier Lyapunov function‐based adaptive fuzzy output feedback control for nonlinear delayed systems with time‐varying full‐state constraints
Author(s) -
Ye Dan,
Wang Kaiyu,
Yang Haijiao,
Zhao Xingang
Publication year - 2020
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.3172
Subject(s) - control theory (sociology) , backstepping , nonlinear system , lyapunov function , fuzzy logic , observer (physics) , bounded function , controller (irrigation) , state observer , fuzzy control system , mathematics , computer science , adaptive control , control (management) , artificial intelligence , biology , mathematical analysis , physics , quantum mechanics , agronomy
Summary In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time‐delay systems with time‐varying full state constraints and input saturation. To overcome the problem of time‐varying constraints, the integral barrier Lyapunov functions (IBLFs) integrating with dynamic surface control (DSC) are applied for the first time to keep the state from violating constraints. The effects of unknown time delays can be removed by using designed Lyapunov‐Krasovskii functions (LKFs). An auxiliary design system is introduced to solve the problem of input saturation. The unknown nonlinear functions are approximated by the fuzzy logic systems (FLS), and the unmeasured states are estimated by a designed fuzzy observer. The novel controller can guarantee that all signals remain semiglobally uniformly ultimately bounded and satisfactory tracking performance is achieved. Finally, two simulation examples illustrate the effectiveness of the presented control methods.