Modified crow search algorithm–based fuzzy control of adjacent buildings connected by magnetorheological dampers considering soil–structure interaction

Abstract

Finding effective means of protecting structures from dynamic hazards is a challenging task and has gained increasing significance. As for the seismically excited adjacent structures, an intelligent control strategy using magnetorheological dampers as connection devices considering soil–structure interaction is presented. First, the calculation model for the coupled structure–soil–structure interaction–magnetorheological damper system is developed, and the motion equation for calculating the seismic responses is then derived. Second, a semiactive control strategy integrating a modified crow search algorithm into a fuzzy logic control is proposed. In this strategy, to accurately calculate the voltage of magnetorheological dampers, the modified crow search algorithm with a hybrid coding strategy, priority selection scheme for target crows, new solution updating method, and guarantee mechanism of the solution feasibility is proposed to design the fuzzy logic control system. The numerical example of 10-story and 20-story coupled buildings demonstrates that soil–structure interaction should be taken into consideration to avoid overestimating the control effect. Besides, the proposed modified crow search algorithm outperforms genetic algorithm in terms of accuracy and robustness. Furthermore, by using magnetorheological dampers to interconnect the coupled structure with soil–structure interaction, dual advantages, that is response reduction and pounding mitigation can be achieved. The proposed modified crow search algorithm–fuzzy logic control method shows comprehensive performance superiority over its competitors, that is passive-off, passive-on, on–off, linear quadratic regulator–clipped voltage law, and linear quadratic Gaussian–clipped voltage law control strategies.

Crow Search Algorithm: Theory, Recent Advances, and Applications

“…In [105], authors employed their new version of CSA in finding the design of the optimum structure. Also, Lin et al [159] used modified CSA with a fuzzy concept to control adjacent con- nected building by magnetorheological dampers concerning soil-structure interaction…”

Optimal Allocation and Control of Magnetorheological Dampers for Enhancing Seismic Performance of the Adjacent Structures Using Whale Optimization Algorithm

“…e control results of the proposed WOA-ALLO-FLC method using only 12 MR dampers are compared with those of on-off control [12], linear quadratic regulator based on clipped voltage law (LQR-CVL) [12] where LQR is a linear quadratic optimal control with the full-state feedback as input that is often used for calculating the desired controlling force [6,13,14], and WOA-FLC methods where only the FLC is optimized with WOA using the proposed encoding scheme. In the latter three control methods, every pair of adjacent floors are connected with two MR dampers.…”

“…ey have become one of the most promising control devices to reduce the vibration responses in the field of engineering [8][9][10]. Katebi and Zadeh [11] and Lin et al [12] employed MR dampers to interconnect the adjacent structures with different kinds of control algorithms. e results validated that MR dampers not only can suppress the structural vibration but also can prevent structures from colliding with each other to a certain extent.…”

“…e simulation results demonstrated the superiority of the PSO-based FLC strategy over other MAs. Lin et al [12] proposed a modified crow search algorithm (CSA) to optimize the FLC parameters for the MR dampers with the consideration of soil-structure interaction. e results validated the effectiveness of this optimal FLC.…”

Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models

“…In the application of MR fluid, bio-inspired computing optimizing algorithm has gained interest as it is a promising approach that can be further developed for new and robust competing techniques. Apart from the Genetic Algorithm, other bio-inspired algorithms, including Grasshopper optimization algorithm [27], shuffled Frog Leaping Algorithm [28], and Crow Search Algorithm [29] have shown potential in describing the MR damper used. However, these algorithms are complicated.…”