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- W2956033701 abstract "This chapter investigates the finite-time neural network event-triggered control issue for a class of nonlinear pure-feedback systems. The dynamic surface control technique is adopted to address the issue of “explosion of complexity” in the backstepping recursive design. Based on an event-triggered mechanism and the approximation property of neural networks, virtual and actual control signals are designed. Under the theoretical framework of finite-time stability, a novel neural network event-triggered dynamic surface control strategy is proposed. The presented control strategy can guarantee that the closed-loop system is semi-globally practically finite-time stable, and the tracking error converges to a small residual set in a finite time. Finally, the effectiveness of theoretical results is verified by means of simulation studies." @default.
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- W2956033701 date "2019-03-16" @default.
- W2956033701 modified "2023-10-13" @default.
- W2956033701 title "Finite-Time Neural Network Event-Triggered Dynamic Surface Control for Nonlinear Pure-Feedback Systems" @default.
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- W2956033701 doi "https://doi.org/10.1007/978-3-030-14350-3_2" @default.
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