Black box model identification of nonlinear input–output models: A Wiener–Hammerstein benchmark

Abstract

This work analyzes the performance of several black box nonlinear model identification techniques for input–output models with polynomial nonlinearities on a benchmark identification problem. The case study, proposed in Schoukens, Suykens, and Ljung (2008), concerns a nonlinear SISO electronic system with a Wiener–Hammerstein structure, originally documented in Vandersteen (1997). The objective being the obtainment of an accurate simulation model, capable of replicating the dynamic behavior of the system without using past measured output data, various output-error approaches have been tested and compared with more standard equation-error techniques. The provided analysis shows that excellent modeling performance can be obtained with these methods even without explicitly taking into account the block structure of the nonlinear system.