Nonlinear control of magnetic suspension system based on RBFNN

Jianyun Cao; Guoping Lu; Gang Feng; Weili Hu

Nonlinear control of magnetic suspension system based on RBFNN

Jianyun Cao
, Guoping Lu
, Gang Feng
, Weili Hu

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

In this paper, nonlinear characteristic of a multivariable magnetic suspension system is formulated, and a modified scheme of nonlinear multivariable internal model control (IMC) is put forward, based on neural network inversion. With Radial Basis Function Neural Network (RBFNN) approximating inversion of the system, the compound system is linearised and decoupled, and IMC can be applied here for this nonlinear magnetic suspension system. In the end, simulations can prove the effectiveness of the improved approach. © 2005 IEEE.

Original language	English
Title of host publication	Proceedings of the 5th International Conference on Control and Automation, ICCA'05
Pages	321-324
Publication status	Published - 2005
Event	5th International Conference on Control and Automation, ICCA 2005 - Budapest, Hungary Duration: 26 Jun 2005 → 29 Jun 2005

Conference

Conference	5th International Conference on Control and Automation, ICCA 2005
Place	Hungary
City	Budapest
Period	26/06/05 → 29/06/05

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@inproceedings{e438335b14ed4bca99aebe9587973879,

title = "Nonlinear control of magnetic suspension system based on RBFNN",

abstract = "In this paper, nonlinear characteristic of a multivariable magnetic suspension system is formulated, and a modified scheme of nonlinear multivariable internal model control (IMC) is put forward, based on neural network inversion. With Radial Basis Function Neural Network (RBFNN) approximating inversion of the system, the compound system is linearised and decoupled, and IMC can be applied here for this nonlinear magnetic suspension system. In the end, simulations can prove the effectiveness of the improved approach. {\textcopyright} 2005 IEEE.",

author = "Jianyun Cao and Guoping Lu and Gang Feng and Weili Hu",

year = "2005",

language = "English",

isbn = "0780391381",

pages = "321--324",

booktitle = "Proceedings of the 5th International Conference on Control and Automation, ICCA'05",

note = "5th International Conference on Control and Automation, ICCA 2005 ; Conference date: 26-06-2005 Through 29-06-2005",

}

Nonlinear control of magnetic suspension system based on RBFNN. / Cao, Jianyun; Lu, Guoping; Feng, Gang et al.
Proceedings of the 5th International Conference on Control and Automation, ICCA'05. 2005. p. 321-324 TA1-2.2.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Nonlinear control of magnetic suspension system based on RBFNN

AU - Cao, Jianyun

AU - Lu, Guoping

AU - Feng, Gang

AU - Hu, Weili

PY - 2005

Y1 - 2005

N2 - In this paper, nonlinear characteristic of a multivariable magnetic suspension system is formulated, and a modified scheme of nonlinear multivariable internal model control (IMC) is put forward, based on neural network inversion. With Radial Basis Function Neural Network (RBFNN) approximating inversion of the system, the compound system is linearised and decoupled, and IMC can be applied here for this nonlinear magnetic suspension system. In the end, simulations can prove the effectiveness of the improved approach. © 2005 IEEE.

AB - In this paper, nonlinear characteristic of a multivariable magnetic suspension system is formulated, and a modified scheme of nonlinear multivariable internal model control (IMC) is put forward, based on neural network inversion. With Radial Basis Function Neural Network (RBFNN) approximating inversion of the system, the compound system is linearised and decoupled, and IMC can be applied here for this nonlinear magnetic suspension system. In the end, simulations can prove the effectiveness of the improved approach. © 2005 IEEE.

UR - https://www.scopus.com/pages/publications/27844469437

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-27844469437&origin=recordpage

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0780391381

SN - 9780780391383

SP - 321

EP - 324

BT - Proceedings of the 5th International Conference on Control and Automation, ICCA'05

T2 - 5th International Conference on Control and Automation, ICCA 2005

Y2 - 26 June 2005 through 29 June 2005

ER -

Nonlinear control of magnetic suspension system based on RBFNN

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