Maximum likelihood iterative identification approaches for multivariable equation-error moving average systems

Abstract

The identification issues of a multivariable system with coloured noises are investigated in this paper. The decomposition strategy is utilised for dimension reduction by transforming a multivariable system into several sub-models. A maximum likelihood least squares-based iterative identification approach is presented to enhance the parameter estimation accuracy by combining the iterative identification technique with the maximum likelihood principle. A simulation example is offered to test the effectiveness of the proposed method.

Keywords:

• Multivariable system
• maximum likelihood
• parameter estimation
• iterative identification
• decomposition

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the the Natural Science Foundation of Colleges and Universities of Jiangsu Province (Grant Nos. 19KJB120012, 19KJB470031), the 135 Engineering of Taizhou Education Bureau [Grant No. 2018TZCJ001], and the Key Topic of Taizhou University (No. TZXY2019ZDKT002) and the National Natural Science Foundation of China (No. 61773181).

Notes on contributors

Huafeng Xia

Huafeng Xia received her B.Sc. degree from the Jiangsu University of Technology (Changzhou, China) in 2003, the M.Sc. degree from Wuhan University of Science and Technology (Wuhan, China) in 2008, and the PhD degree from Jiangnan University (Wuxi, China). From 2003 to 2005, she was a teacher in Jiangyin Huazi Vocatinal School, Jiangyin, Jiangsu Province. From 2008 to now, she is a teacher in Taizhou University, Taizhou, Jiangsu Province. She has been an associate professor in Taizhou University since 2018. Her research interests include system identification.

Li Xie

Li Xie received her BSc, MSc and PhD degrees all from the Jiangnan University (Wuxi, China) in 2007, 2009 and 2013, respectively. She has been an associate professor in the School of Internet of Things Engineering at the Jiangnan University since 2014. Her current research interests include system identification and soft sensor development.

Quanmin Zhu

Quanmin Zhu is a professor in control systems in the Department of Engineering Design and Mathematics, University of the West of England, Bristol, UK. He obtained his M.Sc. in Harbin Institute of Technology, China in 1983 and Ph.D. in Faculty of Engineering, University of Warwick, UK in 1989. His main research interest is in the area of nonlinear system modelling, identification, and control. He has published over 200 papers on these topics, edited five Springer books and one book for the other publisher, and provided consultancy to various industries. Currently Professor Zhu is acting as editor of International Journal of Modelling, Identification and Control, editor of International Journal of Computer Applications in Technology.