Journal
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
Volume 55, Issue 6, Pages 2211-2238Publisher
SPRINGER
DOI: 10.1007/s00158-016-1637-5
Keywords
System identification; Force identification; Firefly algorithm (FA); Nelder-Mead algorithm; Shrinking search space
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In this paper, we present an approach for simultaneous identification of the system parameters and the input dynamic force time history. The inverse problem associated with the system identification is formulated as an optimization problem and is solved using a newly developed dynamic hybrid adaptive firefly algorithm (DHAFA). A modified version of Tikhonov regularization is employed while solving the inverse problem associated with the force identification in order to improve the quality of the solution. Numerical simulation studies have been carried out by solving three distinct numerical examples. Studies presented in this paper indicate that the proposed algorithm is effective in identifying the system parameters as well as the input dynamic force simultaneously and can be effectively used for structural health monitoring purposes. Convergence studies presented in this paper on the newly developed dynamic hybrid firefly algorithm indicate that the proposed algorithm has better convergence characteristics and can be effectively employed for solving complex nonlinear optimization problems associated with system identification.
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