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For the linear dynamic part the subspace identification method with the multivariable output-error state-space algorithm is employed, whereas for the non-linear static part the multi-layer perceptron neural network with Levenberg\u2013Marquardt algorithm is used. The stability and convergence of the proposed method is shown using the Lyapunov direct method and the region solution of the linear matrix inequality (LMI) approach. The proposed method is tested by simulations performed on the continuous stirred tank reactor (CSTR) plant, which is presented by non-linear differential equations. Moreover, the method is applied on the input\u2013output data that are obtained from a practical system of the CSTR plant as well as the pH neutralization plant. The results show significant improvements in online identification of the non-linear dynamic systems compared with the recently reported methods in literature.<\/jats:p>","DOI":"10.1177\/0142331216663618","type":"journal-article","created":{"date-parts":[[2016,8,25]],"date-time":"2016-08-25T22:29:39Z","timestamp":1472164179000},"page":"666-674","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":10,"title":["Online identification of non-linear dynamic systems by Wiener model using subspace method and neural networks"],"prefix":"10.1177","volume":"40","author":[{"given":"Mohsen","family":"Sadeghi","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Iran University of Science and Technology, Tehran 16846-13114, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad","family":"Farrokhi","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Iran 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