Maximum likelihood-based recursive least-squares estimation for multivariable systems using the data filtering technique

ABSTRACT

For multivariable equation-error systems with an autoregressive moving average noise, this paper applies the decomposition technique to transform a multivariable model into several identification sub-models based on the number of the system outputs, and derives a data filtering and maximum likelihood-based recursive least-squares algorithm to reduce the computation complexity and improve the parameter estimation accuracy. A multivariable recursive generalised extended least-squares method and a filtering-based recursive extended least-squares method are presented to show the effectiveness of the proposed algorithm. The simulation results indicate that the proposed method is effective and can produce more accurate parameter estimates than the compared methods.

KEYWORDS:

• Parameter estimation
• maximum likelihood
• data filtering
• multivariable system

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Feng Ding http://orcid.org/0000-0002-2721-2025

Ahmed Alsaedi http://orcid.org/0000-0003-3133-7119

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 61873111], the 111 Project [grant number B12018] and the 135 Engineering of Taizhou Education Bureau [grant number 2018TZCJ001].

Notes on contributors

Huafeng Xia

Huafeng Xia received her B.Sc. degree from the Jiangsu University of Technology (Changzhou, China) in 2003 and the M.Sc. degree from Wuhan University of Science and Technology (Wuhan, China) in 2008. 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 is pursuing for doctor degree at the School of Internet of Things Engineering, Jiangnan University, Wuxi, China. Her research interests include system identification.

Yongqing Yang

Yongqing Yang received the B.S. degree from Anhui Normal University, Wuhu, China, the M.S. degree from Anhui University of Science and Technology, Huainan, China, and the Ph.D. degree from Southeast University, Nanjing, China, in 1985, 1992, and 2007, respectively. He is currently a professor of Jiangnan University. He is the author or coauthor of more than 50 journal papers. His research interests include nonlinear systems, neural networks and optimisation.

Feng Ding

Feng Ding received his BSc degree from the Hubei University of Technology (Wuhan, China) in 1984, and his MSc and PhD degrees both from the Tsinghua University (Beijing, China) in 1991 and 1994, respectively. He has been a professor in the School of Internet of Things Engineering at the Jiangnan University (Wuxi, China) since 2004. His current research interests include system identification and adaptive control. He authored five books on System Identification.

Ahmed Alsaedi

Ahmed Alsaedi obtained his Ph.D. degree from Swansea University (UK) in 2002. He has a broad experience of research in applied mathematics. His fields of interest include dynamical systems, nonlinear analysis involving ordinary differential equations, fractional differential equations, boundary value problems, mathematical modelling, biomathematics, Newtonian and Non-Newtonian fluid mechanics. He has published several articles in peer-reviewed journals. He has supervised several M.S. students and executed many research projects successfully. He is reviewer of several international journals. He served as the chairman of the mathematics department at KAU and presently he is serving as director of the research programme at KAU. Under his great leadership, this programme is running quite successfully and it has attracted a large number of highly rated researchers and distinguished professors from all over the world. He is also the head of NAAM international research group at KAU.

Tasawar Hayat

Tasawar Hayat was born in Khanewal, Punjab, Distinguished National Professor and Chairperson of Mathematics Department at Quaid-I-Azam University is renowned worldwide for his seminal, diversified and fundamental contributions in models relevant to physiological systems, control engineering. He has a honour of being fellow of Pakistan Academy of Sciences, Third World Academy of Sciences (TWAS) and Islamic World Academy of Sciences in the mathematical Sciences.