Fuzzy rule-based neural appointed-time control for uncertain nonlinear systems with aperiodic samplings

作者：

Highlights：

• Realizing a faster convergence time without relying on the initial system values.

• Improving estimates accuracy of uncertainties and avoiding the learning explosion.

• Avoid excessive samplings of control signal without degrading system behaviors.

摘要

•Realizing a faster convergence time without relying on the initial system values.•Improving estimates accuracy of uncertainties and avoiding the learning explosion.•Avoid excessive samplings of control signal without degrading system behaviors.

论文关键词：Fuzzy wavelet neural network,Improved prescribed performance control,State observer,Event-triggered control,Unknown control coefficients

论文评审过程：Received 1 August 2020, Revised 23 November 2020, Accepted 14 December 2020, Available online 24 December 2020, Version of Record 11 January 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.114504