In this work, a novel identification method based on differential evolution algorithm has been applied to bilinear systems and its performance has been compared to that of genetic algorithm. Box-Jenkins system and different type bilinear systems have been identified using differential evolution and genetic algorithms. The simulation results have shown that bilinear systems can be successfully and efficiently identified using these algorithms.

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Generally, memoryless polynomial nonlinear model for nonlinear part and finite impulse response (FIR) model or infinite impulse response model for linear part are preferred in Hammerstein models in literature. In this paper, system identification applications of Hammerstein model that is cascade of nonlinear second order volterra and linear FIR model are studied. Recursive least square algorithm is used to identify the proposed Hammerstein model parameters. Furthermore, the results are compared to identify the success of proposed Hammerstein model and different types of models.