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- W4297153935 abstract "In this article, the dynamic surface control (DSC) based on the event-triggered control (ETC) framework is discussed for the states constrained systems in nonaffine form with disturbances. The uncertain smooth nonlinear terms produced at recursive each step are approximated by the radial basis function neural networks (RBFNNs). An invertible symmetric mapping is adopted to deal with the full state constraints. An auxiliary signal is designed to handle the input unmodeled dynamics. The event-triggered input is constructed in the DSC framework. The stability analysis illustrates all the signals are bounded in the controlled system. Each state is strictly limited within the artificially preset boundary restrictions. A simulation is employed to verify the theoretical findings." @default.
- W4297153935 created "2022-09-27" @default.
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- W4297153935 date "2022-01-01" @default.
- W4297153935 modified "2023-09-26" @default.
- W4297153935 title "Event-Triggered Adaptive Neural Control for Uncertain Constrained Nonlinear Systems" @default.
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- W4297153935 doi "https://doi.org/10.1007/978-981-19-6203-5_6" @default.
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