An enhanced atomic orbital search optimization algorithm for solving the large domain parameter identification problems in nonlinear systems

This paper uses the principle of positronium to improve the atomic orbital search (AOS). To enhance the AOS, the quantum mechanics, and atomic orbital model are combined, called EAOS. By integrating the positron as the opposite solution candidate with the electrons of the atom, the proposed EAOS was developed to enhance the exploration and exploitation of AOS. The efficiency of the proposed improved algorithm has been implemented on benchmark mathematicalfunctions and nonlinear systems identification as an optimization problem. The modified Bouc-Wen model of MR dampers was selected for the system identification problem. Also, the effectiveness of the proposed EAOS was examined by challenging problems of large domain identification problems.Results demonstrate that the new proposed EAOS has a high ability to tackle highly nonlinear problems. Also, the EAOS can preserve its performance for large domain optimization problems

کلیدواژه ها:

parameter identification ، optimization algorithm ، atomic orbital search ، nonlinear system ، Bouc-Wen model ، large domain.