Abstract:A semi-active controller-based neural network for nonlinear benchmark structure equipped with a magnetorheological (MR) damper is presented and evaluated. An inverse neural network model (INV-MR) is constructed ...

A direct adaptive neurocontroller is proposed to reduce structure response to earth vibrations by actively creating an equal but opposite force to that of the first mode force of the structure. While earthquake forces are ...

A semiactive control method for seismically exited nonlinear bench mark building equiped with a magnetorheological damper is presented and evaluated.The magnetorheological dampers generating great interestamong researchers ...

A semi-active controller-based neural network for a 3 story nonlinear benchmark structure equipped with a Magneto Rheological (MR) damper is presented and evaluated. An inverse neural network model (NIMR) is constructed ...

A new neural network (NN) predictive controller (NNPC) algorithm has been developed and tested in

the computer simulation of active control of nonlinear benchmark buildings. Although in classical model

predictive ...

Abstract: Optimal placement of actuators and sensors is an important problem in control of structures that is often

selected without any systematic method. Appropriate placement strongly influences on the performance ...

structure control approach. Simulation results with a 2 kW inverter system confirm the excellent performance of the suggested scheme. The total harmonic distortion and power factor are measured as 2% and 0.99 respectively. Therefore, it is shown...

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and comparing the robustness of structural control systems. Several reliability estimation



methods, procedures and algorithms with various capabilities, accuracy and efficiency have



been suggested in the past. A quantitative...