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SCIENCE CHINA Information Sciences, https://doi.org/10.1007/s11432-019-2680-1

Adaptive Event-Triggered Control for a Class of Nonlinear Systems with Periodic Disturbances

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Abstract

This paper investigates the adaptive event-triggered control problem for a class of nonlinear systems subject to periodic disturbances. To reduce the communication burden, a reliable relative threshold strategy is proposed. Fourier series expansion and radial basis function neural network are combined into a function approximator to model suitable time-varying disturbed function of known periods in strict feedback systems. By combining the Lyapunov stability theory and the backstepping technique, the proposed adaptive control approach ensures that all the signals in the closed-loop system are bounded, and the tracking error can be regulated to a compact set around zero in a finite time. Finally, simulation results are presented to verify the effectiveness of the theoretical results.


Funded by

National Key R&D Program of China (2018YFB1700400)

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