Global and asymptotically efficient identification of nonlinear rational systems via a two-step method

Biqiang Mu, Er-Wei Bai, Wei Xing Zheng

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

Abstract

![CDATA[Identification of nonlinear rational systems defined as the ratio of two nonlinear functions of past inputs and outputs is considered in this paper. Although this problem has a long history, there is still lack of a globally consistent identification algorithm for such identification problem. This paper develops a globally consistent algorithm by the following steps: model transformation, bias analysis, noise variance estimation, and compensation. First, the paper studies the prediction error type estimator (nonlinear least square estimators) and the corresponding solving algorithm (Gauss-Newton algorithms). It is shown that the Gauss-Newton algorithm is locally convergent but actually asymptotically efficient by calculating the Cramér-Rao lower bound under Gaussian observation noises. This motivates that a global and asymptotically efficient estimator can be constructed by combining the proposed globally consistent estimator with the Gauss-Newton algorithm. So, a two-step method is proposed, which consists of first executing the globally consistent algorithm and then applying the Gauss-Newton algorithm with the consistent estimate serving as the initial value. A simulation example is provided to verify the good performance of the proposed two-step method.]]
Original languageEnglish
Title of host publicationProceedings of 2016 35th Chinese Control Conference (CCC 2016), Chengdu, China, 27-29 July 2016
PublisherIEEE
Pages1987-1994
Number of pages8
ISBN (Print)9789881563910
DOIs
Publication statusPublished - 2016
EventChinese Control Conference -
Duration: 27 Jul 2016 → …

Publication series

Name
ISSN (Print)1934-1768

Conference

ConferenceChinese Control Conference
Period27/07/16 → …

Keywords

  • mathematical models
  • nonlinear systems

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