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First, BLA is divided into obtaining front and back linear dynamics of the Wiener\u2010Hammerstein model. Second, a refitting procedure of all parameters is carried out to reduce modelling errors. In this paper, a novel approach to identify Wiener\u2010Hammerstein systems in a single step is proposed. This approach is based on a customized evolutionary algorithm (WH\u2010EA) able to look for the best BLA split, capturing at the same time the process static nonlinearity with high precision. Furthermore, to correct possible errors in BLA estimation, the locations of poles and zeros are subtly modified within an adequate search space to allow a fine\u2010tuning of the model. The performance of the proposed approach is analysed by using a demonstration example and a nonlinear system identification benchmark.<\/jats:p>","DOI":"10.1155\/2018\/1753262","type":"journal-article","created":{"date-parts":[[2018,2,23]],"date-time":"2018-02-23T15:24:19Z","timestamp":1519399459000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["WH\u2010EA: An Evolutionary Algorithm for Wiener\u2010Hammerstein System Identification"],"prefix":"10.1155","volume":"2018","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2935-8458","authenticated-orcid":false,"given":"J.","family":"Zambrano","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9697-2696","authenticated-orcid":false,"given":"J.","family":"Sanchis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1914-7494","authenticated-orcid":false,"given":"J. 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