ROLLOVER PREDICTION AND CONTROL IN HEAVY VEHICLES VIA RECURRENT HIGH ORDER NEURAL NETWORKS

被引：11

作者：

Sanchez, Edgar N. ^{[1
]}

Ricalde, Luis J. ^{[2
]}

Langari, Reza ^{[3
]}

Shahmirzadi, Danial ^{[4
]}

机构：

[1] CINVESTAV, Unidad Guadalajara, Guadalajara 45091, Jal, Mexico

[2] Univ Autonoma Yucatan, Fac Ing, Merida, Yuc, Mexico

[3] Texas A&M Univ, Dept Mech Engn, College Stn, TX 77843 USA

[4] Univ Maryland, Orthopaed Mechanobiol Lab, College Pk, MD 20742 USA

来源：

INTELLIGENT AUTOMATION AND SOFT COMPUTING | 2011年 / 17卷 / 01期

关键词：

Recurrent neural networks; rollover prediction; trajectory tracking; adaptive control; speed-yaw rate control;

D O I：

10.1080/10798587.2011.10643135

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a predictor is developed in order to estimate roll angle and lateral acceleration for tractor-semitrailers. Based on this prediction, an active control system is designed to prevent rollover for these vehicles. In order to develop this control structure, a high order recurrent neural network is used to model the unknown tractor semitrailer system; a learning law is obtained using the Lyapunov methodology. Then a control law, which stabilizes the reference tracking error dynamics, is developed using Control Lyapunov Functions and the inverse optimal control approaches. Via simulations, the control scheme is applied to the speed-only and speed-yaw rate trajectory tracking in a tractor-semitrailer during a cornering situation.

引用

页码：95 / 107

页数：13

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