Journal article
A globally consistent nonlinear least squares estimator for identification of nonlinear rational systems
Automatica (Oxford), Vol.77, pp.322-335
03/2017
DOI: 10.1016/j.automatica.2016.11.009
Abstract
This paper considers identification of nonlinear rational systems defined as the ratio of two nonlinear functions of past inputs and outputs. Despite its long history, a globally consistent identification algorithm remains illusive. This paper proposes a globally convergent identification algorithm for such nonlinear rational systems. To the best of our knowledge, this is the first globally convergent algorithm for the nonlinear rational systems. The technique employed is a two-step estimator. Though two-step estimators are known to produce consistent nonlinear least squares estimates if a N consistent estimate can be determined in the first step, how to find such a N consistent estimate in the first step for nonlinear rational systems is nontrivial and is not answered by any two-step estimators. The technical contribution of the paper is to develop a globally consistent estimator for nonlinear rational systems in the first step. This is achieved by involving model transformation, bias analysis, noise variance estimation, and bias compensation in the paper. Two simulation examples and a practical example are provided to verify the good performance of the proposed two-step estimator.
Details
- Title: Subtitle
- A globally consistent nonlinear least squares estimator for identification of nonlinear rational systems
- Creators
- Biqiang Mu - University of SydneyEr-Wei Bai - University of IowaWei Xing Zheng - University of SydneyQuanmin Zhu - University of the West of England
- Resource Type
- Journal article
- Publication Details
- Automatica (Oxford), Vol.77, pp.322-335
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.automatica.2016.11.009
- ISSN
- 0005-1098
- eISSN
- 1873-2836
- Grant note
- name: President Fund of Academy of Mathematics and Systems Science, CAS, award: 2015-hwyxqnrc-mbq; name: National Key Basic Research Program of China, award: 2014CB845301; DOI: 10.13039/100000001, name: National Science Foundation, award: CNS-1239509; DOI: 10.13039/501100000923, name: Australian Research Council, award: DP120104986; DOI: 10.13039/501100001809, name: National Nature Science Foundation of China, award: 61273188, 61603379
- Language
- English
- Date published
- 03/2017
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197535302771
Metrics
10 Record Views