Optimal Structural Control Using Neural Networks
Publication: Journal of Engineering Mechanics
Volume 126, Issue 2
Abstract
An optimal control algorithm using neural networks is proposed. The controller neural network is trained by a training rule developed to minimize cost function. Both the linear structure and the nonlinear structure can be controlled by the proposed neurocontroller. A bilinear hysteretic model is used to simulate nonlinear structural behavior. Three main advantages of the neurocontroller can be summarized as follows. First, it can control a structure with unknown dynamics. Second, it can easily be applied to nonlinear structural control. Third, external disturbances can be considered in the optimal control. Examples show that structural vibration can be controlled successfully.
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Information & Authors
Information
Published In
Journal of Engineering Mechanics
Volume 126 • Issue 2 • February 2000
Pages: 201 - 205
History
Received: May 5, 1999
Published online: Feb 1, 2000
Published in print: Feb 2000
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