Design for AC servo position loop based on RBF neural network predictive control

DOI

10.2991/meic-15.2015.179How to use a DOI?

Keywords

RBF neural network; predictive control; AC PMSM; machine tool; position control

Abstract

Aiming at wide variations in loads and moment of inertia of the machine tool position servo system, the position loop controller is designed based on RBF neural network control and predictive control. The mathematical model of AC PMSM is established. The predictive model is designed based on controlled autoregressive integral moving average model, obtained the predictive vector and the reference trajectory. The RBF neural network structure is established, tuning PID algorithm is designed. A new control strategy which combined with predictive control and RBF neural network PID control is obtained. Compared with the torque fluctuation, anti-interference ability and tracking properties of the traditional PID control, predictive control ensures that the system tracking performance and RBF neural network control can adjust PID parameters on-line, which guarantees the robustness in the external disturbance and parameter perturbation. The simulation results demonstrate that the RBF neural network predictive controller can guarantee the static and dynamic performance of the system.

Copyright

© 2015, 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  - Ying Zhang
AU  - Ke Zhou
AU  - Yongguang Gong
AU  - Lifeng Chen
PY  - 2015/04
DA  - 2015/04
TI  - Design for AC servo position loop based on RBF neural network predictive control
BT  - Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 784
EP  - 787
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-15.2015.179
DO  - 10.2991/meic-15.2015.179
ID  - Zhang2015/04
ER  -