Robust adaptive NN control for a class of uncertain discrete-time nonlinear MIMO systems

被引：11

作者：

Cui, Yang ^{[1
]}

Liu, Yan-Jun ^{[1
]}

Li, Dong-Juan ^{[2
]}

机构：

[1] Liaoning Univ Technol, Sch Sci, Jinzhou 121001, Liaoning, Peoples R China

[2] Liaoning Univ Technol, Sch Chem & Environm Engn, Jinzhou 121001, Liaoning, Peoples R China

来源：

NEURAL COMPUTING & APPLICATIONS | 2013年 / 22卷 / 3-4期

关键词：

The high-order neural networks; Adaptive control; Nonlinear MIMO systems; Adaptive robust control; OUTPUT-FEEDBACK CONTROL; UNKNOWN CONTROL DIRECTIONS; FUZZY CONTROL; TRACKING CONTROL; OBSERVER; COUPLINGS;

D O I：

10.1007/s00521-011-0766-4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A robust adaptive NN output feedback control is proposed to control a class of uncertain discrete-time nonlinear multi-input-multi-output (MIMO) systems. The high-order neural networks are utilized to approximate the unknown nonlinear functions in the systems. Compared with the previous research for discrete-time MIMO systems, robustness of the proposed adaptive algorithm is obvious improved. Using Lyapunov stability theorem, the results show all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking errors converge to a small neighborhood of zero by choosing the design parameters appropriately.

引用

页码：747 / 754

页数：8

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