Generalised Hammerstein-Wiener System Estimation and a Benchmark Application
نویسندگان
چکیده
This paper examines the use of a so-called “generalised Hammerstein–Wiener” model structure that is formed as the concatenation of an arbitrary number of Hammerstein systems. The latter are taken here to be memoryless nonlinearities followed by linear time invariant dynamics. Hammerstein, Wiener, Hammerstein–Wiener and Wiener–Hammerstein models are all special cases of this structure. The parameter estimation of this model is investigated by using a standard prediction error criterion coupled with a robust gradient based search algorithm. This approach is profiled using a Wiener– Hammerstein benchmark example, which illustrates it to be effective and, via Monte–Carlo simulation, relatively robust against capture in local minima.
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