Event-triggered adaptive neural network tracking control with dynamic gain and prespecified tracking accuracy for a class of pure-feedback systems

HIGHLIGHTS

  • who: Shuiyan Wu and collaborators from the School of Mathematics and Statistics, Xianyang Normal University, Xianyang, China have published the paper: Event-Triggered Adaptive Neural Network Tracking Control with Dynamic Gain and Prespecified Tracking Accuracy for a Class of Pure-Feedback Systems, in the Journal: Symmetry 2022, 14, 1949. of /2022/
  • what: The aim of this paper is to design an ET adaptive NN controller to meet the following objectives: (a) All the signals in the closed-loop systems are bounded on [0, +u221e); (b) Tracking error y - yr falls into a prespecified e-neighbourhood . . .

     

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