Designing a General Neurocontroller for Water Towers
Publication: Journal of Engineering Mechanics
Volume 126, Issue 6
Abstract
This study deals with the capabilities of artificial neural networks in learning to control water towers of different structural properties that are subjected to earthquakes. To this end, water towers were considered as single-degree-of-freedom systems. First, a number of water towers of different structural properties were controlled by the predictive optimal control method, and then the data collected through this control were used in the training of a general neural network controller, called the general neurocontroller. Capabilities of the general neurocontroller were tested in the control of a number of water towers with structural parameters different from, but in the range of, those used in its training. One of the aims of this study was the introduction of general neurocontrollers as ready-to-use devices that may be used in the design of actively controlled structures, in this case, water towers. Results of this numerical study were promising.
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Information & Authors
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Published In
Journal of Engineering Mechanics
Volume 126 • Issue 6 • June 2000
Pages: 582 - 587
History
Received: Nov 3, 1998
Published online: Jun 1, 2000
Published in print: Jun 2000
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