Partially-coupled gradient-based iterative algorithms for multivariable output-error-like systems with autoregressive moving average noises

The parameter estimation problem of multivariable output-error-like systems with autoregressive moving average noises is investigated in this study, and the primary system is segregated into some subsystems and a subsystem generalised extended gradient-based iterative algorithm is presented accordin...

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Bibliographic Details
Published in:IET control theory & applications 2020-11, Vol.14 (17), p.2613-2627
Main Authors: Ma, Hao, Zhang, Xiao, Liu, Qinyao, Ding, Feng, Jin, Xue-Bo, Alsaedi, Ahmed, Hayat, Tasawar
Format: Article
Language:English
Subjects:
autoregressive moving average noises
autoregressive moving average processes
common parameter estimation vectors
common parameter vector
coupled relationships
coupling identification concept
gradient methods
iterative methods
multivariable control systems
multivariable output‐error‐like systems
optimal estimate
parameter estimation
parameter estimation problem
partially coupled generalised extended gradient‐based iterative algorithm
partially coupled subsystem
primary system
redundant estimates
Research Article
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Summary:The parameter estimation problem of multivariable output-error-like systems with autoregressive moving average noises is investigated in this study, and the primary system is segregated into some subsystems and a subsystem generalised extended gradient-based iterative algorithm is presented according to the decomposition technique. Nevertheless, there exists the common parameter vector in each subsystem, which increases the calculation. By taking the mean value of the common parameter estimation vectors of the subsystems as the optimal estimate of the current iteration, and substituting it into the next iteration, a partially coupled subsystem generalised extended gradient-based iterative algorithm is proposed. Furthermore, in the cause of further deepening the coupled relationships between the common parameter estimation vectors of two subsystems and to reduce the computational cost and the redundant estimates, a partially coupled generalised extended gradient-based iterative algorithm is presented by making use of the coupling identification concept. Finally, the simulation results show that the coupled gradient-based iterative algorithms are effective.
ISSN:1751-8644
1751-8652
DOI:10.1049/iet-cta.2019.1027