Dynamic Structure Neural Network for Stable Adaptive Control of Nonlinear Systems

被引：0
|
作者：
Lei, Jingye [1 ]
机构：
[1] Honghe Univ, Coll Engn, Mengzi 661100, Yunnan, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2011, PT III | 2011年 / 6677卷
关键词：
adaptive control; neural network; nonlinear system; predictive control; gradient descent rule; simulation;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper an adaptive control strategy based on neural network for a class of nonlinear system is analyzed. A simplified algorithm is presented with the technique in generalized predictive control theory and the gradient descent rule to accelerate learning and improve convergence. Taking the neural network as a model of the system, control signals are directly obtained by minimizing the cumulative differences between a setpoint and output of the model. The applicability in nonlinear system is demonstrated by simulation experiments.
引用
收藏
页码：104 / 111
页数：8
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