Designing a General Neurocontroller for Water Towers

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 s...

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Bibliographic Details
Published in:Journal of engineering mechanics 2000-06, Vol.126 (6), p.582-587
Main Authors: Joghataie, Abdolreza, Vahidi, Ardalan
Format: Article
Language:English
Subjects:
Airport towers
Applied sciences
Computer science
control theory
systems
Control theory. Systems
Design engineering
Exact sciences and technology
Mathematical models
Mechanics
Neural networks
Optimal control
Optimization
Seismic phenomena
TECHNICAL PAPERS
Training
Water towers
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Summary: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.
ISSN:0733-9399
1943-7889
DOI:10.1061/(ASCE)0733-9399(2000)126:6(582)