Vehicle Suspension Vibration Control Using Recurrent Neural Networks

被引：0
|
作者：
Guan, Huawei [1 ]
Le, Xinyi [1 ]
Wang, Jun [1 ,2 ]
机构：
[1] Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Hong Kong, Peoples R China
[2] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
来源：
FIFTH INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROL AND INFORMATION PROCESSING (ICICIP) | 2014年
基金：
中国国家自然科学基金;
关键词：
FEEDBACK-CONTROL SYSTEMS; ROBUST POLE ASSIGNMENT; SYMMETRIC MATRIX; STATE-FEEDBACK; EIGENVECTORS; EIGENVALUES; COMPUTATION;
D O I：
暂无
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 presents an application of vibration control to a half-car model using recurrent neural networks. The robust vibration control is formulated as equality constrained optimization problem. Simulation results show that the close-loop system has good response performance in the presence of disturbances generated by an isolated bump. The study shows potential in using neural networks for the active vibration control in precision machine design.
引用
收藏
页码：435 / 440
页数：6
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