Multi-Innovation Stochastic Gradient Parameter and State Estimation Algorithm for Dual-Rate State-Space Systems with d-Step Time Delay
Joint Authors
Zhu, Quanmin
Gu, Ya
Liu, Jicheng
Zhu, Peiyi
Chou, Yongxin
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-13
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
This paper presents a multi-innovation stochastic gradient parameter estimation algorithm for dual-rate sampled state-space systems with d-step time delay by the multi-innovation identification theory.
Considering the stochastic disturbance in industrial process and using the gradient search, a multi-innovation stochastic gradient algorithm is proposed through expanding the scalar innovation into an innovation vector in order to obtain more accurate parameter estimates.
The difficulty of identification is that the information vector in the identification model contains the unknown states.
The proposed algorithm uses the state estimates of the observer instead of the state variables to realize the parameter estimation.
The simulation results indicate that the proposed algorithm works well.
American Psychological Association (APA)
Gu, Ya& Zhu, Quanmin& Liu, Jicheng& Zhu, Peiyi& Chou, Yongxin. 2020. Multi-Innovation Stochastic Gradient Parameter and State Estimation Algorithm for Dual-Rate State-Space Systems with d-Step Time Delay. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142737
Modern Language Association (MLA)
Gu, Ya…[et al.]. Multi-Innovation Stochastic Gradient Parameter and State Estimation Algorithm for Dual-Rate State-Space Systems with d-Step Time Delay. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1142737
American Medical Association (AMA)
Gu, Ya& Zhu, Quanmin& Liu, Jicheng& Zhu, Peiyi& Chou, Yongxin. Multi-Innovation Stochastic Gradient Parameter and State Estimation Algorithm for Dual-Rate State-Space Systems with d-Step Time Delay. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142737
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142737