Adaptive RBF Neural-Network-Based Design Strategy for Non-Strict-Feedback Nonlinear Systems by Using Integral Lyapunov Functions

Adaptive RBF Neural-Network-Based Design Strategy for Non-Strict-Feedback Nonlinear Systems by Using Integral Lyapunov Functions

This paper develops an adaptive radical basis function neural-network (NN)-based controller design strategy that uses integral Lyapunov functions for a class of non-strict-feedback nonlinear systems subject to perturbations. The design difficulty caused by the non-strict-feedback system structure is...

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Bibliographic Details
Main Authors: Xiao-Mei Wang, Ben Niu, Guo-qiang Wu, Jun-Qing Li, Pei-yong Duan, Dong Yang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Nonlinear systems
non-strict-feedback structure
integral Lyapunov functions
neural networks
adaptive tracking control
Online Access:https://ieeexplore.ieee.org/document/8554078/

Internet

https://ieeexplore.ieee.org/document/8554078/

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