Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process
Joint Authors
Li, Dazi
Xie, Qianwen
Jin, Qibing
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
A new strategy for internal model control (IMC) is proposed using a regression algorithm of quasilinear model with extreme learning machine (QL-ELM).
Aimed at the chemical process with nonlinearity, the learning process of the internal model and inverse model is derived.
The proposed QL-ELM is constructed as a linear ARX model with a complicated nonlinear coefficient.
It shows some good approximation ability and fast convergence.
The complicated coefficients are separated into two parts.
The linear part is determined by recursive least square (RLS), while the nonlinear part is identified through extreme learning machine.
The parameters of linear part and the output weights of ELM are estimated iteratively.
The proposed internal model control is applied to CSTR process.
The effectiveness and accuracy of the proposed method are extensively verified through numerical results.
American Psychological Association (APA)
Li, Dazi& Xie, Qianwen& Jin, Qibing. 2015. Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073142
Modern Language Association (MLA)
Li, Dazi…[et al.]. Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1073142
American Medical Association (AMA)
Li, Dazi& Xie, Qianwen& Jin, Qibing. Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073142
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073142