• Smart Structures and Systems
• /
• v.23 no.1
• /
• pp.1-14
• /
• 2019

Control algorithms are the most important aspects in successful control of structures against earthquakes. In recent years, intelligent control methods rather than classical control methods have been more considered by researchers, due to some specific capabilities such as handling nonlinear and complex systems, adaptability, and robustness to errors and uncertainties. However, due to lack of learning ability of fuzzy controller, it is used in combination with a genetic algorithm, which in turn suffers from some problems like premature convergence around an incorrect target. Therefore in this research, the introduction and design of the Fuzzy Cooperative Coevolution (Fuzzy CoCo) controller and Adaptive Neural-Fuzzy Inference System (ANFIS) have been innovatively presented for semi-active seismic control. In this research, in order to improve the seismic behavior of structures, a semi-active control of building using Magneto Rheological (MR) damper is proposed to determine input voltage of Magneto Rheological (MR) dampers using ANFIS and Fuzzy CoCo. Genetic Algorithm (GA) is used to optimize the performance of controllers. In this paper, the design of controllers is based on the reduction of the Park-Ang damage index. In order to assess the effectiveness of the designed control system, its function is numerically studied on a 9-story benchmark building, and is compared to those of a Wavelet Neural Network (WNN), fuzzy logic controller optimized by genetic algorithm (GAFLC), Linear Quadratic Gaussian (LQG) and Clipped Optimal Control (COC) systems in terms of seismic performance. The results showed desirable performance of the ANFIS and Fuzzy CoCo controllers in considerably reducing the structure responses under different earthquakes; for instance ANFIS and Fuzzy CoCo controllers showed respectively 38 and 46% reductions in peak inter-story drift ($J_1$) compared to the LQG controller; 30 and 39% reductions in $J_1$ compared to the COC controller and 3 and 16% reductions in $J_1$ compared to the GAFLC controller. When compared to other controllers, one can conclude that Fuzzy CoCo controller performs better.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.8 no.3
• /
• pp.63-76
• /
• 2004

This paper presents LRB-based hybrid base isolation systems employing additional active/semiactive control devices for mitigating earthquake-induced vibration of a cable-stayed 29 bridge. Hybrid base isolation systems could improve the control performance compared with the passive type-base isolation system such as LRB-installed bridge system due to multiple control devices are operating. In this paper, the additional response reduction by the two typical additional control devices, such as active type hydraulic actuators controlled by LQG algorithm and semiactive-type magnetorheological dampers controlled by clipped-optimal algorithm, have been evaluated bypreliminarily investigating the slightly modified version of the ASCE phase I benchmark cable-stayed bridge problem (i.e., the installation of LRBs to the nominal cable-stayed bridge model of the problem). It shows from the numerical simulation results that all the LRB based hybrid seismic isolation systems considered are quite effective to mitigate the structural responses. In addition, the numerical results demonstrate that the LRB based hybrid seismic isolation systems employing MR dampers have the robustness to some degree of the stiffness uncertainty of in the structure, whereas the hybrid system employing hydraulic actuators does not. Therefore, the feasibility of the hybrid base isolation systems employing semiactive additional control devices could be more appropriate in realfor full-scale civil infrastructure applications is clearly verified due to their efficacy and robustness.