Design for AC servo position loop based on RBF neural network predictive control
- 10.2991/meic-15.2015.179How to use a DOI?
- RBF neural network; predictive control; AC PMSM; machine tool; position control
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.
- © 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/).
Cite this article
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 -