Parameter estimation for pseudo-linear systems using the auxiliary model and the decomposition technique

Feng Ding; Feifei Wang; Ling Xu; Tasawar Hayat; Ahmed Alsaedi

Parameter estimation for pseudo-linear systems using the auxiliary model and the decomposition technique

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Author(s): Feng Ding ^{1, 2} ; Feifei Wang ² ; Ling Xu ² ; Tasawar Hayat ^{1, 3} ; Ahmed Alsaedi ¹
- Affiliations: 1: Nonlinear Analysis and Applied Mathematics (NAAM) Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia ;
  2: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, People's Republic of China ;
  3: Department of Mathematics, Quaid-I-Azam University, Islamabad 44000, Pakistan
Source: Volume 11, Issue 3, 03 February 2017, p. 390 – 400
DOI: 10.1049/iet-cta.2016.0491 , Print ISSN 1751-8644, Online ISSN 1751-8652

Received 05/05/2016, Accepted 04/11/2016, Revised 10/10/2016, Published 07/11/2016

This study focuses on the parameter identification problems of pseudo-linear systems. The main goal is to present recursive least squares (RLS) estimation methods based on the auxiliary model identification idea and the decomposition technique. First, an auxiliary model-based RLS algorithm is given as a comparison. Second, to improve the computation efficiency, a decomposition-based RLS algorithm is presented. Then for the system identification with missing data, an interval-varying RLS algorithm is derived for estimating the system parameters. Furthermore, this study uses the decomposition technique to reduce the computational cost in the interval-varying RLS algorithm and introduces the forgetting factors to track the time-varying parameters. The simulation results show that the proposed algorithms can work well.

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