Sliding mode control with neural network for active magnetic bearing system

Conference paper (2019)

Authors

Z. Cao Southeast University, DC systems, Energy conversion & Storage - EEMCS
J. Dong DC systems, Energy conversion & Storage - EEMCS
F.M. Wani Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
H. Polinder Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
P. Bauer DC systems, Energy conversion & Storage - EEMCS
Fei Peng Southeast University
Yunkai Huang Southeast University
Research Group
DC systems, Energy conversion & Storage (EEMCS) (TU Delft)
Copyright: © 2019 Z. Cao, J. Dong, F.M. Wani, H. Polinder, P. Bauer, Fei Peng, Yunkai Huang
DOI: https://doi.org/10.1109/IECON.2019.8926808
Neural network Sliding mode control Magnetic bearing
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Published Date

2019

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Electrical Sustainable Energy

Research Group

DC systems, Energy conversion & Storage

Abstract

A novel controller design procedure is proposed for a 5-degree-of-freedom (DOF) active magnetic bearing (AMB) system, based on sliding mode control (SMC) and neural network (NN). The SMC is used to achieve high robustness and fast response while the NN can compensate unmodeled uncertainty and external disturbance by on-line tuning algorithm. The proposed controller is compared with the well-tuned PID controller by simulations. The simulation results show the superior performance of the proposed controller.