Design and evaluation of hysteresis models for structural systems using a fuzzy adaptive charged system search

Many hysteresis models have been proposed for the simulation of the nonlinear behavior of structures each of which has certain advantages depending on specific applications and desired objectives. The Bouc-Wen-Baber-Noori model is one of the hysteresis models that has been utilized for a wide range of applications. However, the parameter tuning of this model has been conducted based on expert knowledge, which has not led to the development of a precise nonlinear model. The main contribution of this paper is to propose a metaheuristic-based parametric identification process for the design of the Bouc-Wen-Baber-Noori hysteresis model and evaluate the results by using some established experimental investigation methods. To fulfill this aim, the Fuzzy Adaptive Charged System Search (F-CSS) is proposed for optimization in which a fuzzy-logic-based parameter tuning process is utilized to achieve better performance in comparison with the standard Charged System Search algorithm (CSS). For nonlinear dynamic analysis, an Iterative Hysteretic Analysis (IHA) process is also introduced for conducting the precise analysis of the structure with exact solutions. Comparing the metaheuristic-based results to the experimental findings demonstrates that the proposed algorithm is capable of providing very competitive results. Besides, the proposed adaptive method is capable of producing very competitive results in comparison with different optimization algorithms.