Mixture Basis Function Approximation and Neural Network Embedding Control for Nonlinear Uncertain Systems with Disturbances

Mixture Basis Function Approximation and Neural Network Embedding Control for Nonlinear Uncertain Systems with Disturbances

A neural network embedding learning control scheme is proposed in this paper, which addresses the performance optimization problem of a class of nonlinear system with unknown dynamics and disturbance by combining with a novel nonlinear function approximator and an improved disturbance observer (DOB)...

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Bibliographic Details
Main Authors: Le Ma, Qiaoyu Zhang, Tianmiao Wang, Xiaofeng Wu, Jie Liu, Wenjuan Jiang
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Mathematics
Subjects:
mixture basic functions approximating
neural network embedding control
control performance optimization
disturbance observer
Online Access:https://www.mdpi.com/2227-7390/11/13/2823

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