Optimal fuzzy control of radial active magnetic bearing systems

Author

Yu, Shin-Shiung ; Wu, Shinq-Jen ; Lee, Tsu-Tian

Author_Institution

Dept. of Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan

Volume

3

fYear

2003

fDate

16-20 July 2003

Firstpage

1393

Abstract

In this paper, a neural-fuzzy approach to develop the optimal fuzzy control of a highly nonlinear radial current-controlled active magnetic bearing (AMB) systems is proposed. A linear self-constructing neural fuzzy inference network is proposed to neural-fuzzy modeling the radial current-controlled AMB system first. Then, the corresponding optimal fuzzy control design scheme is obtained to stabilize the AMB system with minimize current consumption. Simulation results show that the proposed optimal fuzzy controller can operate in widely range of shaft position.

Keywords

fuzzy control; magnetic bearings; neurocontrollers; nonlinear control systems; optimal control; current consumption; neural-fuzzy approach; nonlinear radial active magnetic bearing systems; optimal fuzzy control; self-constructing neural fuzzy inference network; shaft position; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Magnetic levitation; Nonlinear control systems; Nonlinear magnetics; Optimal control; Shafts; Turbines;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Robotics and Automation, 2003. Proceedings. 2003 IEEE International Symposium on

Print_ISBN

0-7803-7866-0

Type

conf

DOI

10.1109/CIRA.2003.1222201

Filename

1222201