Smart fuzzy control of reinforced concrete structures excited by collision-type forces

The purpose of this study is to develop a smart controller for energy dissipation and damage mitigation of collision-excited reinforced concrete structures. This study is the first attempt to apply fuzzy logic theory to smart reinforced concrete structures equipped with MR dampers under collision forces for structural impact hazard mitigation. The parameters of the fuzzy controller are optimized using a backpropagation neural network. To train the fuzzy controller, a number of experiments were conducted using a smart reinforced concrete beam under a variety of impact loads. The smart reinforced concrete beam is equipped with a magnetorheological (MR) damper, accelerometers, linear variable differential transformer (LVDT), strain gages, and a voltage-current converter. It is implemented using National Instruments hardware with the LabView software. A proportional integral derivative controller (PID) is used as a baseline. It was shown from the comparisons of the fuzzy with the PID controllers that the smart fuzzy controller is an effective way to mitigate the complex impact response of reinforced concrete structures employing an MR damper.