Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

SAGETRACK

Sign In to gain access to subscriptions and/or personal tools.
Journal of Intelligent Material Systems and Structures
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Jeng, C. A.
Right arrow Articles by Lin, J. N.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Multi-Mode Control of Structures by Using Neural Networks with Marquardt Algorithms

C. A. Jeng

Department of Mechanical Engineering, I-Shou University, Taiwan, ROC

S. M. Yang

J. N. Lin

Institute of Aeronautics and Astronautics, National Cheng Kung University, Taiwan, ROC

This paper presents an integrated approach of identification, estimation and vibration control of smart structures by using neural networks with Marquardt adaptation algorithm. An identification neural network is first constructed to model the system dynamics of a composite laminate structure embedded with piezoelectric sensor and actuator. Based on the identification network, a neural controller is then developed to meet the vibration suppression performance specified by a reference model. In addition, an estimation neural network is also developed that enables the measurement of a single piezoelectric sensor to represent the state variables of displacement and velocity of the structure. The neural controller can then minimize the structure vibration by using a pair of piezoelectric sensors and actuators. Experimental verification shows that the vibration amplitude of the smart structure under two-mode harmonic excitation and random excitation can be reduced by 80% and 60%, respectively.

Journal of Intelligent Material Systems and Structures, Vol. 8, No. 12, 1035-1043 (1997)
DOI: 10.1177/1045389X9700801204
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?