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.

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