Nowadays, vibration control of structures is considered as a challenging field among scientists and engineers. Structural damage and financial losses due to recent earthquakes in different countries have more than ever before accentuated the importance of controlling earthquake-induced vibrations. In recent years, semi-active control has been introduced as an efficient and reliable type of structural control which provides the reliability of passive control and flexibility of active control systems at the same time. In this study, the performance of a semi-active tuned mass damper (TMD) with adaptive magnetorheological (MR) damper is investigated using type-1 and -2 fuzzy controllers for seismic vibration mitigation of an 11-degree of freedom building model. The TMD is installed on the roof and the MR damper is located on the 11th story. The MR damper has a capacity of producing a 1000 kN control force. The fuzzy system is designed based on the acceleration and velocity of the top floor determining the input voltage needed to produce the control force based on accelerating or decelerating movements of structure. The seismic performance of semi-active type-2 controller, which considers the uncertainties related to input variables, is higher than that of the type-1 fuzzy controller. The type-2 fuzzy controller is capable of reducing further the maximum displacement, acceleration, and base shear of the structure by 11.7, 14, and 11.2%, respectively, compared to the type-1 fuzzy controller.
SUMMARY The effectiveness of tuned liquid column–gas damper, TLCGD, on the suppression of seismic‐induced vibrations of steel jacket platforms is evaluated in this study. TLCGD is an interesting choice in the case of jacket platforms because it is possible to use the structural elements as the horizontal column of the TLCGD. In this study, optimum parameters of the TLCGD are obtained, considering nonlinear damping of the TLCGD and water–structure interaction between jacket platform and sea water. Equation of motions and other related formulas are derived, and using a SimuLink model, the frequency and the head loss coefficient of the TLCGD are optimized. Results are in general agreement with those obtained in earlier studies for typical building structures. However, effects of period of the structure and ground motion characteristics on the optimum parameters are also evaluated in this study. Results show that until a particular threshold for the mass ratio, the higher the mass ratio, the higher the efficiency of the damper. After that, by increasing the mass ratio, there is no improvement on the damper efficiency. It is also found that PGA and frequency content of a ground motion have no important effect on the optimum frequency ratio, but they have a noticeable effect on the optimum head loss coefficient. Besides, frequency content has some effect on the TLCGD efficiency. It is shown that the optimum frequency of a TLCGD is uncoupled with the area ratio and the head loss coefficient, and they have no effect on the optimum frequency ratio. Copyright © 2011 John Wiley & Sons, Ltd.
This research presents designing a control system to reduce seismic responses of structures. Semi-active control of a magnetorheological (MR) damper is used to improve seismic behavior of a 3-story building implementing neural-fuzzy controller made of adaptive neuro-fuzzy inference system (ANFIS) to determine damper input voltage. Both premise and consequent parameters of fuzzy membership and output functions of ANFIS have the ability for training and improvement but most researchers have focused on just consequent parameters. In order to optimize the controller performance, an approach is proposed in this paper where both premise and consequent parameters of fuzzy functions in an ANFIS network are adjusted simultaneously by genetic algorithm (GA). In order to assess the effectiveness of the designed control system, its function is numerically studied on a benchmark 3-story building and is compared to those of a neural network predictive control (NNPC) algorithm, linear quadratic Gaussian (LQG) and clipped optimal control (COC) systems in terms of seismic performance. The results showed desirable performance of the (ANFIS +GA + membership functions + result function) ANFIS–GA–MFR controller in considerably reducing the structure responses under different earthquakes. The proposed controller showed 30 and 39% reductions in peak story drift (J1) and normed story drift (J4) respectively compared to the NNPC controller, 32 and 44% reductions in J1 and J4 respectively compared to the LQG controller, and 27 and 38% reductions in J1 and J4 respectively compared to the COC controller. The proposed controller effectively reduced acceleration and base shear level compared to the uncontrolled state and had a performance relatively similar to those of three other controllers – for instance, it reduced the maximum level acceleration (J2) 10% higher than COC. Also, the results showed that the ANFIS–GA–MFR controller has more efficiency than the basic ANFIS controller, on average about 20%.
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