Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism
Joint Authors
Chun, Semin
Maruta, Ichiro
Sugie, Toshiharu
Chae, Minji
Kim, Tae-Hyoung
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-27
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems.
To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established.
A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail.
Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO) is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed.
This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process.
This is one of the distinguishing features of the proposed method.
The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria.
Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.
American Psychological Association (APA)
Kim, Tae-Hyoung& Maruta, Ichiro& Sugie, Toshiharu& Chun, Semin& Chae, Minji. 2017. Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1190401
Modern Language Association (MLA)
Kim, Tae-Hyoung…[et al.]. Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism. Mathematical Problems in Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1190401
American Medical Association (AMA)
Kim, Tae-Hyoung& Maruta, Ichiro& Sugie, Toshiharu& Chun, Semin& Chae, Minji. Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1190401
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190401