DocumentCode :
1513782
Title :
Robust Nonsingular Terminal Sliding-Mode Control for Nonlinear Magnetic Bearing System
Author :
Chen, Syuan-Yi ; Lin, Faa-Jeng
Author_Institution :
Dept. of Electr. Eng., Nat. Central Univ., Chungli, Taiwan
Volume :
19
Issue :
3
fYear :
2011
fDate :
5/1/2011 12:00:00 AM
Firstpage :
636
Lastpage :
643
Abstract :
This study presents a robust nonsingular terminal sliding-mode control (RNTSMC) system to achieve finite time tracking control (FTTC) for the rotor position in the axial direction of a nonlinear thrust active magnetic bearing (TAMB) system. Compared with conventional sliding-mode control (SMC) with linear sliding surface, terminal sliding-mode control (TSMC) with nonlinear terminal sliding surface provides faster, finite time convergence, and higher control precision. In this study, first, the operating principles and dynamic model of the TAMB system using a linearized electromagnetic force model are introduced. Then, the TSMC system is designed for the TAMB to achieve FTTC. Moreover, in order to overcome the singularity problem of the TSMC, a nonsingular terminal sliding-mode control (NTSMC) system is proposed. Furthermore, since the control characteristics of the TAMB are highly nonlinear and time-varying, the RNTSMC system with a recurrent Hermite neural network (RHNN) uncertainty estimator is proposed to improve the control performance and increase the robustness of the TAMB control system. Using the proposed RNTSMC system, the bound of the lumped uncertainty of the TAMB is not required to be known in advance. Finally, some experimental results for the tracking of various reference trajectories demonstrate the validity of the proposed RNTSMC for practical TAMB applications.
Keywords :
Hermitian matrices; magnetic bearings; magnetic variables control; nonlinear control systems; recurrent neural nets; robust control; variable structure systems; RNTSMC; TAMB control system; finite time tracking control; linearized electromagnetic force model; nonlinear thrust active magnetic bearing system; recurrent Hermite neural network; robust nonsingular terminal sliding-mode control; rotor position; time-varying system; Control systems; Convergence; Electromagnetic modeling; Magnetic levitation; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear magnetics; Robust control; Sliding mode control; Uncertainty; Hermite polynomials; magnetic bearing system; nonsingular terminal sliding-mode; recurrent neural network; tracking control;
fLanguage :
English
Journal_Title :
Control Systems Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6536
Type :
jour
DOI :
10.1109/TCST.2010.2050484
Filename :
5483156
Link To Document :
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