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- W3180763728 abstract "Abstract This paper investigates the problem of event‐triggered adaptive output‐feedback control for multi‐input and multi‐output (MIMO) uncertain nonlinear systems with time‐varying full state constraints. A tangent‐type nonlinear mapping function is proposed to transform the state‐constrained system into a new one free of constraints, such that the time‐varying full state constraints are never violated. Radial basis function neural networks are introduced to compensate for the unknown functions. A state observer is established to estimate the unmeasured states. A suitable event‐triggering rule is presented to determine when to transmit control laws. Through Lyapunov analyses, all closed‐loop signals are proved to be semiglobally uniformly ultimately bounded, and time‐varying full state constraints are never violated. Finally, simulations are presented to evaluate the efficacy of the proposed approach." @default.
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- W3180763728 date "2021-07-07" @default.
- W3180763728 modified "2023-10-17" @default.
- W3180763728 title "Event‐triggered adaptive output‐feedback control for nonlinear state‐constrained systems using tangent‐type nonlinear mapping" @default.
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- W3180763728 doi "https://doi.org/10.1002/asjc.2599" @default.
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