Research on the Adaptive Sliding Control of Permanent Magnet Linear Synchronous Motor in Neural Network

DOI

10.2991/iccasm.2012.231How to use a DOI?

Keywords

Linear motor, Neural network, Sliding control, Chattering

Abstract

When the permanent magnet linear synchronous motor (PMLSM) direct drive system, the system has the characteristics of nonlinear, motor parameter time-variance and vulnerable disturbance, an adaptive sliding mode controller based on neural network is designed. The controller consists of two neural networks, one is used for sliding equivalent control and the other for sliding switch control, so as to effectively guarantees the system fast tracking performance for a given signal. The controller can restrain the system parameters perturbation and external resistance changes, and weakening the sliding mode control system chattering. The simulation results show that the adaptive sliding mode controller based on neural network can improve the system robustness for parametric perturbation and external disturbance, and possess better dynamic stability and tracking performance

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hongjun Zhu
PY  - 2012/08
DA  - 2012/08
TI  - Research on the Adaptive Sliding Control of Permanent Magnet Linear Synchronous Motor in Neural Network
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 907
EP  - 910
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.231
DO  - 10.2991/iccasm.2012.231
ID  - Zhu2012/08
ER  -