Identification of Hammerstein systems with piecewise nonlinearities with memory

In this paper, we propose an identification method of Hammerstein systems with piecewise nonlinearities with memory, which is based on statistical technique. This model is useful because it has characteristics of both Hammerstein systems and hybrid systems. We employ an identification method using pseudo-random binary sequences (PRBS) inputs for decoupling the identification of nonlinear block with that of piecewise-affine (PWA) dynamic block. In addition, we also employ statistical techniques for identifying the PWA model and the hysteresis model. The validity of the method is demonstrated through numerical simulations.