Neural networks modelling and generalised predictive control for an autonomous underwater vehicle

被引：3
|
作者：
Xu, Jianan [1 ]
Zhang, Mingjun [1 ]
Wang, Yujia [1 ]
机构：
[1] Harbin Engn Univ, Coll Mech & Elect Engn, Harbin 150001, Heilongjiang, Peoples R China
来源：
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL | 2010年 / 11卷 / 1-2期
关键词：
autonomous underwater vehicle; AUV; generalised predictive control; GPC; modified Elman neural networks; MENNs;
D O I：
10.1504/IJMIC.2010.035282
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper investigates the application of neural networks-based generalised predictive motion control for an autonomous underwater vehicle (AUV). The modified Elman neural networks (MENNs) are used as the multi-step predictive model, and the fused identification model is proposed to improve the predictive and control precision. The MENNs online learning improves the control system adaptability to the unpredictable operating environment for AUV. Simulations on AUV yaw velocity control are concluded to illustrate the effectiveness of the proposed control scheme.
引用
收藏
页码：79 / 86
页数：8
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