Semi‐active control for eccentric structures with MR damper based on hybrid intelligent algorithm

Abstract

In this paper, an application of the hybrid intelligent control algorithm to semi‐active control of the magnetorheological (MR) damper is presented for engineering structures. The control signal is optimized directly by the µGA approach to obtain the numerical relation between the control signal and the system output. This relation is then stored in the weight value of a trained artificial neural network, which can be available for another structure subjected to other seismic inputs. The results of a numerical example indicate that the semi‐active control of the MR damper based on the hybrid algorithm can efficiently reduce the structural responses induced by an earthquake. Copyright © 2007 John Wiley & Sons, Ltd.

Advances in bidirectional modeling and structural control

“…The hybrid intelligent control algorithm applied to semi-active control of the magnetorheological (MR) damper is presented in [39]. It is subjected to bidirectional seismic wave.…”

Application of self-tuning Gaussian networks for control of civil structures equipped with magnetorheological dampers

“…The adaptive parameters are chosen to guarantee convergence of the GRF network based on the error. Hence, uncertainties on external loadings from both the desired and current dynamics are cancelled out in (6). The term k depends on the uncertainty on the error on the applied force u b and a constant.…”

“…Magnetorheological (MR) dampers have been proposed in the literature for control of civil structures because of their capability to perform almost as well as active control schemes, while requiring only a fraction of the power input 2,3 .They are also considered to be robust and fail-safe 4 , providing enhanced protection for vibration mitigation during natural hazards. Their hysteretic behavior has been extensively studied and successfully modeled 5 , but their complex dynamic behavior renders complicated the mapping of the required voltage for a desired force 6 . Even when such mapping is possible, knowledge of the dynamic properties of the structure is required.…”

Optimal control of structures under earthquake excitation based on the colonial competitive algorithm

“…In the field of structural control, GAs have been employed to find gain matrix for the optimal controller (Kundu and Kawata, ), reduced order feedback control (Kim and Ghaboussi, ) and optimal damper distribution (Wongprasert and Symans, ), and optimize the different parameters of an active tuned mass damper controller (Pourzeynali et al ., ). Li and Chang () proposed a hybrid control method to control the magnetorheological damper that the control signal optimized using the μGA. Cha and Agrawal () applied GA to determine optimal coefficients of the polynomial equations for the calculation of control force.…”