Abstract
This paper addresses the parameter identification problem of a fractional order system with a known structure. Thus, based on the variational iteration method, its shown that the identification of the parameters can be formulated as an optimization problem. The objective function is the L-2-norm of the error between the measured and the model outputs, and the unknown model parameters are the decision (optimization) variables. Then, the resulting optimization problem is solved using a PSO algorithm. The effectiveness of the proposed approach is demonstrated by two application examples. In each application, the measurements are generated by simulation run by assuming a known parameters and the identification problem consists in estimating the values of these parameters from noisy measurements.