Application Study of ILC with Fuzzy Neural Network in Shaking Table Control System

DOI

10.2991/iske.2007.99How to use a DOI?

Keywords

FNN, ILC, system identification, shaking table.

Abstract

This paper proposes a new approach to improve the control precision of shaking table control system, in which the fuzzy neural network (FNN) technique and iterative learn control (ILC) are combined and developed a new control technique. A FNN inverse model is built and is identified through a white noise with appropriate peak values and frequency range. Then better control effect is obtained by ILC than Remote Parameter Control (RPC). This technique is capable of improving the system precision and adaptability, and reducing the effect of structural load’s dynamic characteristic.

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Jianqiu Chen
AU  - Xinzheng Zhang
AU  - Ping Tan
AU  - Fulin Zhou
PY  - 2007/10
DA  - 2007/10
TI  - Application Study of ILC with Fuzzy Neural Network in Shaking Table Control System
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 580
EP  - 585
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.99
DO  - 10.2991/iske.2007.99
ID  - Chen2007/10
ER  -