Identification of nonlinear systems using Clonal Selection algorithm

In this work, clonal selection algorithm (CSA) has been applied to adaptive identification of nonlinear systems and compared its performance to that of genetic algorithm (GA). Nonlinear Box-Jenkins system which is frequently used as a benchmark example for testing in literature and a parametric nonlinear bilinear system have been identified using these algorithms. The simulation results have shown that nonlinear systems can be identified using CSA with low modeling error.