Wiener Model Based System Identification Based on CRPSO Algorithm

An efficient and accurate method has been proposed in this manuscript to identify a Output Error (OE) structure based Wiener model with Craziness based Particle Swarm Optimization (CRPSO) algorithm. The accuracy and the precision of the identification scheme have been justified with the achieved bias and variance values, respectively, of the estimated parameters. Mean square error (MSE) of the output is considered as the performance measures or the fitness for the CRPSO algorithm. The various statistical measures associated with MSE confirm the superior performance of the proposed CRPSO based identification of the Hammerstein system. Accurate identification of the parameters associated with the linear as well as nonlinear block with the noisy environment ensures the robustness and stability of the overall system.