Designing a general neurocontroller for water towers

This study deals with the capabilities of artificial neural networks in lea rning to control water towers of different structural properties that are s ubjected to earthquakes. To this end, water towers were considered as singl e-degree-of-freedom systems. First, a number of water towers of different s tructural properties were controlled by the predictive optimal control meth od, and then the data collected through this control were used in the train ing of a general neural network controller, called the general neurocontrol ler. 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 t hat may be used in the design of actively controlled structures, in this ca se, water towers. Results of this numerical study were promising.