Abstract
In this study, multi-story structures with different combinations (on each floor and only the first floor) of active tendon control systems driven by a proportional–integral–derivative (PID) controller were actively controlled. The PID parameters, Kp (proportional gain), Td (derivative gain), and Ti (integral gain) for each structure, were optimally tuned by using both the harmony search algorithm (HS) and flower pollination algorithm (FPA), which are metaheuristic algorithms. In two different active-controlled structures, which are formed according to the position of the PID, the structural responses under near-fault records defined in FEMA P-695 are examined to determine the appropriate feedback which was applied for displacement, velocity, acceleration, and total acceleration. The performance of the different feedback strategies on these two active-controlled structures is evaluated. As a result, the acceleration feedback is suitable for all combinations of the active control system with a PID controller. The HS algorithm outperforms the optimum results found according to the FPA.
Highlights
flower pollination algorithm (FPA) is a metaheuristic algorithm inspired by the pollination of flowers and it was developed by Yang [20]
In Case 1, the active control is placed only on the first floor. The structural responses such as displacement, velocity, acceleration, and total acceleration on the first floor are measured with a sensor according to the desired feedback to calculate the control signal and the corresponding control force which is applied to the first floor
The optimization code including the mathematical expressions of metaheuristic algorithms optimizing the design variables and minimizing the objective function taken as the performance index of control was written in MATLAB [21]
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The utilization of active mass dampers and active tendons to reduce structural reactions in tall structures [2,3], the relationship between the control forces and the structural responses [4], time delay effect [5], and the investigation of various feedback strategies for active-controlled structures [6,7]. The attainment of effective solutions in the nonlinear active-controlled structures with artificial neural networks and the use of the metaheuristic algorithms to calculate the parameters of the PID, H2 , and Hinf are the other stochastic based methods in the active control [8,9,10]. It was determined that the different feedback control strategies vary the structural responses where active control provides differently. The use of both HS and FPA is suitable for the fast and successful detection of a correct feedback strategy during the design phase of the structures
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